Fast positioning for vision assisted positioning

Abstract

Aspects presented herein may enable a UE to improve (e.g., reduce) convergence time for visually assisted positioning by enabling the UE to use images embedded with location information. In one aspect, a UE receives a list of visual features and a location of each visual feature in the list of visual features from a reference device, a server, or a map. The UE identifies, via at least one camera, at least one visual feature in an area, where the at least one visual feature is included in the visual feature list, where the area is within a threshold distance of the UE. The UE estimates a location of the UE based on the identified at least one visual feature in the region and the location corresponding to the at least one visual feature.

Description

Cross-reference to related applications

[0001] This application claims the benefit of U.S. non-provisional patent application serial number 18 / 453,705, filed August 22, 2023, entitled “RAPID LOCALIZATION FOR VISION-AIDED POSITIONING”, the entire contents of which are expressly incorporated herein by reference. Technical Field

[0002] This disclosure relates generally to communication systems, and more specifically to wireless communication relating to positioning. Background Technology

[0003] Wireless communication systems are widely deployed to provide a variety of telecommunications services, such as telephone, video, data, messaging, and broadcasting. Typical wireless communication systems may employ multiple access technologies capable of supporting communication with multiple users by sharing available system resources. Examples of such multiple access technologies include Code Division Multiple Access (CDMA) systems, Time Division Multiple Access (TDMA) systems, Frequency Division Multiple Access (FDMA) systems, Orthogonal Frequency Division Multiple Access (OFDMA) systems, Single Carrier Frequency Division Multiple Access (SC-FDMA) systems, and Time Division Synchronous Code Division Multiple Access (TD-SCDMA) systems.

[0004] These multiple access technologies have been adopted in various telecommunications standards to provide a common protocol that enables different wireless devices to communicate at the city, national, regional, and even global levels. An example telecommunications standard is 5G New Radio (NR). 5G NR is part of the Continuous Evolution of Mobile Broadband (CEM) program issued by the 3rd Generation Partnership Project (3GPP) to meet new requirements associated with latency, reliability, security, scalability (e.g., with the Internet of Things (IoT),) and other requirements. 5G NR includes services associated with enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). Some aspects of 5G NR can be based on the 4G Long Term Evolution (LTE) standard. Further improvements to 5G NR technology are needed. Furthermore, these improvements can also be applied to other multiple access technologies and telecommunications standards that adopt these technologies.

[0005] In some scenarios, when vision-assisted localization / vision-based localization begins (or is triggered / activated), a certain amount of convergence time can be specified for precise localization due to inertial measurement unit (IMU) bias calibration and feature tracking. Therefore, the aspects presented in this paper can improve (e.g., reduce) the convergence time of vision-assisted localization / vision-based localization by enabling localization devices to use images embedded with location information to eliminate (common) perception errors in localization devices. Summary of the Invention

[0006] The following is a simplified summary of one or more aspects to provide a basic understanding of these aspects. This summary is not a comprehensive overview of all conceived aspects. It neither identifies key or essential elements of all aspects nor describes the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed descriptions that follow.

[0007] In one aspect of this disclosure, a method, computer-readable medium, and apparatus are provided. The apparatus receives a list of visual features and the location of each visual feature in the list from a reference device, server, or map. The apparatus identifies at least one visual feature in a region via at least one camera, wherein the at least one visual feature is included in the list of visual features, and wherein the region is within a threshold distance of a user equipment (UE). The apparatus estimates the location of the UE based on the identified at least one visual feature in the region and the location corresponding to the at least one visual feature.

[0008] In one aspect of this disclosure, a method, computer-readable medium, and apparatus are provided. The apparatus estimates the six degrees of freedom (6DOF) of a reference device. The apparatus transmits a list of visual features and the position of each visual feature in the list, the 6DOF of the reference device, and a set of Global Navigation Satellite System (GNSS) measurements.

[0009] To achieve the foregoing and related objectives, one or more aspects may include the features fully described below and specifically pointed out in the claims. The following description and drawings set forth some exemplary features of one or more aspects in detail. However, these features indicate only a few of the various ways in which the principles of the various aspects may be employed. Attached Figure Description

[0010] Figure 1 This is a diagram illustrating an example of a wireless communication system and an access network.

[0011] Figure 2A This is an illustration of an example of the first frame according to various aspects of this disclosure.

[0012] Figure 2B This is a diagram illustrating examples of downlink (DL) channels within a subframe according to various aspects of this disclosure.

[0013] Figure 2C This is an illustration of an example of a second frame according to various aspects of this disclosure.

[0014] Figure 2DThis is a diagram illustrating examples of uplink (UL) channels within a subframe according to various aspects of this disclosure.

[0015] Figure 3 This is a diagram illustrating examples of base stations and user equipment (UEs) in an access network.

[0016] Figure 4 This is a diagram illustrating an example of UE positioning based on reference signal measurements.

[0017] Figure 5 This is an illustration illustrating examples of Global Navigation Satellite System (GNSS) positioning according to various aspects of this disclosure.

[0018] Figure 6 This is an illustration of examples of real-time dynamic (RTK) positioning based on various aspects of this disclosure.

[0019] Figure 7 This is an illustration illustrating examples of camera-assisted positioning according to various aspects of this disclosure.

[0020] Figure 8 These are illustrations illustrating examples of navigation applications according to various aspects of this disclosure.

[0021] Figure 9 This is a communication flow that exemplifies various aspects of collaborative visual-assisted localization based on shared environmental features according to this disclosure.

[0022] Figure 10 This is an illustration illustrating examples of collaborative visual-assisted localization based on artificial / virtual features according to various aspects of this disclosure.

[0023] Figure 11 This is an illustration illustrating examples of visually assisted localization based on feature matching with a map, according to various aspects of this disclosure.

[0024] Figure 12 This is an illustration of examples of UE time (dynamic) model enhancements using maps according to various aspects of this disclosure.

[0025] Figure 13 This is a diagram illustrating example Kalman filtering according to various aspects of this disclosure.

[0026] Figure 14 This is a flowchart of a wireless communication method.

[0027] Figure 15 This is a flowchart of a wireless communication method.

[0028] Figure 16 These are illustrations illustrating specific hardware implementations used for example devices and / or network entities.

[0029] Figure 17 This is a flowchart of a wireless communication method.

[0030] Figure 18 This is a flowchart of a wireless communication method.

[0031] Figure 19 This is a diagram illustrating an example of a hardware implementation used for an example network entity. Detailed Implementation

[0032] The aspects presented herein can improve (e.g., reduce) the convergence time of vision-assisted localization (such as vision-assisted precise localization (VAPP)). The aspects presented herein can provide rapid localization for vision-assisted localization by enabling images embedded with location information to be used to eliminate (common) perception errors in localization devices (e.g., during Global Navigation Satellite System (GNSS) outages). In one aspect of this disclosure, the convergence time of vision-based localization can be reduced based on the use of common visual features (e.g., collaborative VAPP using common visual features), wherein the localization device (e.g., user equipment (UE), camera, vehicle, localization engine, etc.) can select a set of common environmental features in the vicinity for rapid localization (e.g., for determining location and / or attitude). In some specific implementations, the localization device may also use created and customized artificial features when such common features are not detected / unavailable. In another aspect of this disclosure, convergence time for vision-based positioning can be reduced by map data assistance (e.g., high-definition (HD) map assistance), wherein the positioning device can perform feature matching with the map (e.g., HD map) to obtain an external precise location source, perform UE temporal (dynamic) model enhancement using the map, and / or perform radio frequency (RF) based (GNSS) positioning error modeling based on the map, etc.

[0033] The aspects presented in this paper relate to enhancements related to Visual Assisted Precision Positioning (VAPP). The aspects presented in this paper include the following aspects / features: (1) Collaborative VAPP using common visual features—(a) selecting common environmental features in the vicinity for rapid positioning (elevation and location), and (b) creating and customizing artificial features when common features are not detected; (2) HD map-assisted VAPP—(a) feature matching with HD maps to obtain external precise location sources, and (b) using HD maps for UE temporal (dynamic) model enhancement, and (c) RF-based (GNSS) positioning error modeling based on HD maps.

[0034] The detailed descriptions following, illustrated with reference to the accompanying drawings, describe various configurations and do not represent the only configurations in which the concepts described herein can be practiced. To provide a thorough understanding of the various concepts, the detailed descriptions include specific details. However, these concepts can be practiced without these specific details. In some instances, well-known structures and components are shown in block diagram form to avoid obscuring these concepts.

[0035] Various apparatuses and methods are presented with reference to several aspects of a telecommunications system. These apparatuses and methods are described in detail below and illustrated in the accompanying drawings by various blocks, components, circuits, processes, algorithms, etc. (collectively, “elements”). These elements may be implemented using electronic hardware, computer software, or any combination thereof. Whether these elements are implemented as hardware or software depends on the specific application and the design constraints imposed on the system as a whole.

[0036] As an example, an element, any part of an element, or any combination of elements may be implemented as a "processing system" including one or more processors. When multiple processors are implemented, the multiple processors may perform functions individually or in combination. Examples of processors include microprocessors, microcontrollers, graphics processing units (GPUs), central processing units (CPUs), application processors, digital signal processors (DSPs), reduced instruction set computing (RISC) processors, system-on-a-chip (SoCs), baseband processors, field-programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gate logic, discrete hardware circuits, and other suitable hardware configured to perform the various functionalities described throughout this disclosure. One or more processors in the processing system can execute software. Whether referred to as software, firmware, middleware, microcode, hardware description language, or other terms, software should be broadly interpreted as instructions, instruction sets, code, code segments, program code, programs, subroutines, software components, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, or any combination thereof.

[0037] Therefore, in one or more example aspects, specific implementations, and / or use cases, the described functionality may be implemented in hardware, software, or any combination thereof. If implemented in software, the functionality may be stored or encoded as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media. Storage media may be any available medium accessible to a computer. By way of example, such computer-readable media may include random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), optical disc storage devices, magnetic disk storage devices, other magnetic storage devices, combinations of these types of computer-readable media, or any other medium that can be used to store computer-executable code in the form of instructions or data structures accessible to a computer.

[0038] While aspects, implementations, and / or use cases are described herein by way of example, additional or different aspects, implementations, and / or use cases may arise in many different arrangements and scenarios. The aspects, implementations, and / or use cases described herein can be implemented across many different platform types, devices, systems, shapes, sizes, and package arrangements. For example, aspects, implementations, and / or use cases may arise via integrated chip implementations and other devices based on non-modular components (e.g., end-user devices, vehicles, communication devices, computing devices, industrial equipment, retail / purchasing devices, medical devices, AI-enabled devices, etc.). While some examples may or may not be specific to a use case or application, the described examples may exhibit broad applicability. Aspects, implementations, and / or use cases can range from chip-level or modular components to non-modular, non-chip-level implementations, and further to aggregated, distributed, or original equipment manufacturer (OEM) devices or systems incorporating one or more of the technologies described herein. In some practical settings, devices incorporating the described aspects and features may also include additional components and features for implementing and practicing the claimed and described aspects. For example, the transmission and reception of wireless signals necessarily involve multiple components for analog and digital purposes (e.g., hardware components including antennas, RF chains, power amplifiers, modulators, buffers, processors, interleavers, adders / summers, etc.). The techniques described herein can be practiced in a wide variety of devices, chip-level components, systems, distributed arrangements, aggregated or decomposed components, end-user equipment, etc., of various sizes, shapes, and configurations.

[0039] Communication systems, such as 5G NR systems, can be deployed in various ways with a variety of components or parts. In a 5G NR system or network, network nodes, network entities, network mobility elements, radio access network (RAN) nodes, core network nodes, network elements or network equipment (such as base stations (BS)), or one or more units (or components) performing base station functions can be implemented in aggregated or decomposed architectures. For example, BSs (such as Node B (NB), evolved NB (eNB), NR BS, 5G NB, access point (AP), transmit / receive point (TRP), or cell, etc.) can be implemented as aggregated base stations (also known as standalone BS or monolithic BS) or decomposed base stations.

[0040] Aggregated base stations can be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node. Decentralized base stations can be configured to utilize a protocol stack that is physically or logically distributed across two or more units, such as one or more central or centralized units (CUs), one or more distributed units (DUs), or one or more radio units (RUs). In some aspects, the CU may be implemented within a RAN node, and one or more DUs may co-located with the CU, or alternatively, may be geographically or virtually distributed across one or more other RAN nodes. DUs may be implemented to communicate with one or more RUs. Each of the CU, DU, and RU may be implemented as a virtual unit, namely a virtual central unit (VCU), a virtual distributed unit (VDU), or a virtual radio unit (VRU).

[0041] Base station operation or network design can take into account the aggregation characteristics of base station functionality. For example, decomposed base stations can be utilized in Integrated Access Backhaul (IAB) networks, Open Radio Access Networks (O-RAN (such as network configurations initiated by the O-RAN Alliance)), or Virtualized Radio Access Networks (vRAN, also known as Cloud Radio Access Networks (C-RAN)). Decomposition can include distributing functionality across two or more units in various physical locations, as well as virtually distributing the functionality of at least one unit, which enables flexibility in network design. The various units of a decomposed base station or decomposed RAN architecture can be configured to communicate wirelessly with at least one other unit.

[0042] Figure 1Figure 100 illustrates an example of a wireless communication system and access network. The illustrated wireless communication system includes a decomposed base station architecture. The decomposed base station architecture may include one or more CUs 110, which may communicate directly with the core network 120 via a backhaul link, or indirectly with the core network 120 via one or more decomposed base station units, such as a near real-time (near-RT) RAN Intelligent Controller (RIC) 125 via an E2 link, or a non-real-time (non-RT) RIC 115 associated with a Service Management and Orchestration (SMO) framework 105, or both. CUs 110 may communicate with one or more DUs 130 via a corresponding midhaul link (such as an F1 interface). DUs 130 may communicate with one or more RUs 140 via a corresponding fronthaul link. RUs 140 may communicate with a corresponding UE 104 via one or more radio frequency (RF) access links. In some implementations, a UE 104 may be served simultaneously by multiple RUs 140.

[0043] Each of the units (i.e., CU 110, DU 130, RU 140, and near-RT RIC 125, non-RT RIC 115, and SMO frame 105) may include or be coupled to one or more interfaces configured to receive or transmit signals, data, or information (collectively, signals) via wired or wireless transmission media. Each of the units, or an associated processor or controller providing instructions to the communication interfaces of these units, may be configured to communicate with one or more other units via transmission media. For example, these units may include wired interfaces configured to receive signals or transmit signals to one or more other units via wired transmission media. Additionally, these units may include wireless interfaces that may include receivers, transmitters, or transceivers (such as RF transceivers) configured to receive signals via wireless transmission media and / or transmit signals to one or more other units.

[0044] In some aspects, the CU 110 can host one or more higher-level control functions. Such control functions may include Radio Resource Control (RRC), Packet Data Convergence Protocol (PDCP), Serving Data Adaptation Protocol (SDAP), etc. Each control function can be implemented using an interface configured to signal to other control functions hosted by the CU 110. The CU 110 can be configured to handle user plane functionality (i.e., Central Unit-User Plane (CU-UP)), control plane functionality (i.e., Central Unit-Control Plane (CU-CP)), or a combination thereof. In some implementations, the CU 110 can be logically divided into one or more CU-UP units and one or more CU-CP units. When implemented in an O-RAN configuration, the CU-UP units can communicate bidirectionally with the CU-CP units via an interface such as an E1 interface. The CU 110 can be implemented to communicate with the DU 130 for network control and signaling, as needed.

[0045] DU 130 may correspond to a logical unit that includes one or more base station functions for controlling the operation of one or more RU 140s. In some aspects, DU 130 may at least partially host one or more of the Radio Link Control (RLC) layer, Media Access Control (MAC) layer, and one or more high physical (PHY) layers (such as modules for forward error correction (FEC) encoding and decoding, scrambling, modulation, demodulation, etc.) according to functional splits (such as those defined by 3GPP). In some aspects, DU 130 may also host one or more low PHY layers. Each layer (or module) may be implemented using an interface configured to communicate signals with other layers (and modules) hosted by DU 130 or with control functions hosted by CU 110.

[0046] Lower-layer functionality can be implemented by one or more RU 140s. In some deployments, an RU140 controlled by a DU 130 may correspond to a logical node that at least partially hosts RF processing functions or low-PHY layer functions (such as performing Fast Fourier Transform (FFT), Inverse FFT (iFFT), digital beamforming, Physical Random Access Channel (PRACH) extraction and filtering, etc.) based on functional decomposition such as lower-layer functional decomposition, or both. In this architecture, the RU 140 can be implemented to handle over-the-air (OTA) communications with one or more UEs 104. In some specific implementations, the real-time and non-real-time aspects of control plane and user plane communications with the RU 140 may be controlled by the corresponding DU 130. In some scenarios, this configuration allows the DU 130 and CU 110 to be implemented in cloud-based RAN architectures such as vRAN architectures.

[0047] SMO framework 105 can be configured to support RAN deployment and provisioning of both non-virtualized and virtualized network elements. For non-virtualized network elements, SMO framework 105 can be configured to support the deployment of dedicated physical resources for RAN coverage requirements, which can be managed via operation and maintenance interfaces such as the O1 interface. For virtualized network elements, SMO framework 105 can be configured to interact with a cloud computing platform such as Open Cloud (O-Cloud) 190 to perform network element lifecycle management (such as instantiating virtualized network elements) via a cloud computing platform interface such as the O2 interface. Such virtualized network elements may include, but are not limited to, CU 110, DU 130, RU 140, and near-RT RIC 125. In some implementations, SMO framework 105 can communicate with hardware aspects of the 4G RAN, such as Open eNB (O-eNB) 111, via the O1 interface. Additionally, in some implementations, SMO framework 105 can communicate directly with one or more RU 140s via the O1 interface. SMO framework 105 may also include a non-RT RIC 115 configured to support the functionality of SMO framework 105.

[0048] The non-RT RIC 115 can be configured to include logical functions enabling non-real-time control and optimization of RAN elements and resources, including artificial intelligence (AI) / machine learning (ML) workflows for model training and updates, or policy-based guidance for applications / features in the near-RT RIC 125. The non-RT RIC 115 can be coupled to or communicate with the near-RT RIC 125, such as via an A1 interface. The near-RT RIC 125 can be configured to include logical functions enabling near real-time control and optimization of RAN elements and resources via data collection and actions through an interface such as an E2 interface, connecting one or more CU 110s, one or more DU 130s, or both, and O-eNBs to the near-RT RIC 125.

[0049] In some implementations, to generate AI / ML models to be deployed in the near-RT RIC 125, the non-RT RIC 115 may receive parameters or external enrichment information from an external server. This information can be utilized by the near-RT RIC 125 and can be received from non-network data sources or network functions at the SMO framework 105 or the non-RT RIC 115. In some examples, the non-RT RIC 115 or the near-RT RIC 125 may be configured to tune RAN behavior or performance. For example, the non-RT RIC 115 may monitor long-term trends and patterns in performance and employ AI / ML models to perform corrective actions via the SMO framework 105 (such as reconfiguration via O1) or by creating RAN management policies (such as A1 policies).

[0050] At least one of CU 110, DU 130, and RU 140 may be referred to as base station 102. Therefore, base station 102 may include one or more of CU 110, DU 130, and RU 140 (each component is indicated by a dashed line to indicate that each component may or may not be included in base station 102). Base station 102 provides UE 104 with an access point to core network 120. Base station 102 may include macro cells (high-power cellular base stations) and / or small cells (low-power cellular base stations). Small cells include femtocells, picocells, and microcells. A network that includes both small cells and macro cells may be referred to as a heterogeneous network. A heterogeneous network may also include an evolved home node B (eNB) (HeNB), which can provide service to a restricted group referred to as a closed subscriber group (CSG). The communication link between RU 140 and UE 104 may include uplink (UL) transmission (also known as reverse link) from UE 104 to RU 140 and / or downlink (DL) transmission (also known as forward link) transmission from RU 140 to UE 104. The communication link may utilize multiple-input multiple-output (MIMO) antenna techniques, including spatial multiplexing, beamforming, and / or transmit diversity. The communication link may use one or more carriers. For each direction, the total number of carriers used for transmission can be up to [number missing]. Yx MHz ( x For each carrier allocated in carrier aggregation (of component carriers), base station 102 / UE 104 can use up to [number] carriers. Y A spectrum with a bandwidth of MHz (e.g., 5MHz, 10MHz, 15MHz, 20MHz, 100MHz, 400MHz, etc.). Carriers may be adjacent to each other or may not be adjacent to each other. Carrier allocation may be asymmetric with respect to DL and UL (e.g., more or fewer carriers may be allocated to DL compared to UL). Component carriers may include primary component carriers and one or more secondary component carriers. The primary component carrier may be referred to as the primary cell (PCell) and the secondary component carrier may be referred to as the secondary cell (SCell).

[0051] Some UEs 104 can communicate with each other using device-to-device (D2D) communication link 158. D2D communication link 158 can use DL / UL wireless wide area network (WWAN) spectrum. D2D communication link 158 can use one or more sidelink channels, such as Physical Sidelink Broadcast Channel (PSBCH), Physical Sidelink Discovery Channel (PSDCH), Physical Sidelink Shared Channel (PSSCH), and Physical Sidelink Control Channel (PSCCH). D2D communication can be performed through various wireless D2D communication systems, such as Bluetooth. ™ (Bluetooth is a trademark of the Bluetooth Special Interest Group (SIG), and is based on the IEEE 802.11 standard for Wi-Fi.) ™ (Wi-Fi is a trademark of the Wi-Fi Alliance), LTE, or NR.

[0052] The wireless communication system may also include a Wi-Fi AP 150, which communicates with the UE 104 (also referred to as a Wi-Fi station (STA)) via a communication link 154, for example, in an unlicensed spectrum such as 5 GHz. When communicating in unlicensed spectrum, the UE 104 / AP 150 may perform a free channel assessment (CCA) to determine whether the channel is available before communication.

[0053] The electromagnetic spectrum is typically subdivided into various categories, bands, channels, etc., based on frequency / wavelength. In 5G NR, two initial operating bands have been designated as frequency ranges FR1 (410MHz to 7.125GHz) and FR2 (24.25GHz to 52.6GHz). Although a portion of FR1 is greater than 6GHz, in various documents and articles, FR1 is often (interchangeably) referred to as the "sub-6GHz" band. Similar naming issues sometimes occur with FR2, which is often (interchangeably) referred to as the "millimeter wave" band in documents and articles, although this is distinct from the Extremely High Frequency (EHF) band (30GHz to 300GHz) designated as "millimeter wave" by the International Telecommunication Union (ITU).

[0054] The frequencies between FR1 and FR2 are generally referred to as mid-band frequencies. Recent 5G NR studies have identified the operating bands used for these mid-band frequencies as the frequency range designation FR3 (7.125 GHz to 24.25 GHz). Bands falling within FR3 can inherit FR1 and / or FR2 characteristics, and thus can effectively extend the features of FR1 and / or FR2 to mid-band frequencies. Furthermore, higher frequency bands are currently being explored to extend 5G NR operation beyond 52.6 GHz. For example, three higher operating bands have been identified as the frequency range designations FR2-2 (52.6 GHz to 71 GHz), FR4 (71 GHz to 114.25 GHz), and FR5 (114.25 GHz to 300 GHz). Each of these higher frequency bands falls within the EHF band.

[0055] In view of the above, unless otherwise specifically stated, the term "below 6 GHz" as used herein can broadly refer to frequencies less than 6 GHz, within FR1, or including intermediate frequency band frequencies. Furthermore, unless otherwise specifically stated, the term "millimeter wave" as used herein can broadly refer to frequencies that can include intermediate frequency band frequencies, within FR2, FR4, FR2-2 and / or FR5, or within the EHF band.

[0056] Base station 102 and UE 104 may each include multiple antennas (such as antenna elements, antenna panels, and / or antenna arrays) to facilitate beamforming. Base station 102 may transmit beamformed signals 182 to UE 104 in one or more transmit directions. UE 104 may receive beamformed signals from base station 102 in one or more receive directions. UE 104 may also transmit beamformed signals 184 to base station 102 in one or more transmit directions. Base station 102 may receive beamformed signals from UE 104 in one or more receive directions. Base station 102 / UE 104 may perform beamforming training to determine the optimal receive and transmit directions for each of base station 102 / UE 104. The transmit and receive directions of base station 102 may be the same or different. The transmit and receive directions of UE 104 may be the same or different.

[0057] Base station 102 may include and / or be referred to as gNB, Node B, eNB, access point, transceiver base station, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP, network node, network entity, network equipment, or some other suitable terminology. Base station 102 may be implemented as an integrated access and backhaul (IAB) node, relay node, sidelink node, aggregated (monolithic) base station with baseband units (BBU) (including CU and DU) and RU, or may be implemented as a decomposed base station including one or more of CU, DU, and / or RU. A collection of base stations that may include decomposed base stations and / or aggregated base stations may be referred to as Next Generation (NG) RAN (NG-RAN).

[0058] The core network 120 may include Access and Mobility Management Function (AMF) 161, Session Management Function (SMF) 162, User Plane Function (UPF) 163, Unified Data Management (UDM) 164, one or more location servers 168, and other functional entities. AMF 161 is the control node that handles signaling between UE 104 and the core network 120. AMF 161 supports registration management, connection management, mobility management, and other functions. SMF 162 supports session management and other functions. UPF 163 supports packet routing, packet forwarding, and other functions. UDM 164 supports authentication and key agreement (AKA) credential generation, user identity processing, access authorization, and subscription management. One or more location servers 168 are exemplified as including a Gateway Mobile Location Center (GMLC) 165 and a Location Management Function (LMF) 166. However, generally, one or more location servers 168 may include one or more location / positioning servers, which may include one or more of GMLC 165, LMF 166, Position Determination Entity (PDE), Serving Mobile Location Center (SMLC), Mobile Location Center (MPC), etc. GMLC 165 and LMF 166 support UE location services. GMLC 165 provides an interface for clients / applications (e.g., emergency services) to access UE location information. LMF 166 receives measurement and auxiliary information from NG-RAN and UE 104 via AMF 161 to calculate the location of UE 104. NG-RAN may use one or more positioning methods to determine the location of UE 104. Positioning UE 104 may involve signal measurement, location estimation, and optional speed calculation based on these measurements. Signal measurement may be performed by UE 104 and / or base station 102 serving UE 104. The measured signals may be based on one or more of the following systems / signals / sensors: Satellite Positioning System (SPS) 170 (e.g., one or more of Global Navigation Satellite System (GNSS), Global Positioning System (GPS), Non-Terrestrial Network (NTN) or other position / location systems), LTE signals, Wireless Local Area Network (WLAN) signals, Bluetooth signals, Terrestrial Beacon System (TBS), sensor-based information (e.g., barometric pressure sensor, motion sensor), NR Enhanced Cell ID (NR E-CID) method, NR signals (e.g., multiple round-trip time (multiple RTT), DL departure angle (DL-AoD), DL time difference of arrival (DL-TDOA), UL time difference of arrival (UL-TDOA), and UL angle of arrival (UL-AoA) positioning) and / or other systems / signals / sensors.

[0059] Examples of UE 104 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, GPS devices, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, tablet devices, smart devices, wearable devices, vehicles, electricity meters, air pumps, large or small kitchen appliances, healthcare devices, implants, sensors / actuators, displays, or any other similarly functional device. Some UEs in UE 104 may be referred to as IoT devices (e.g., parking meters, air pumps, toasters, vehicles, heart monitors, etc.). UE 104 may also be referred to as a station, mobile station, subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, mobile phone, user agent, mobile client, client, or some other suitable terminology. In some scenarios, the term UE may also be applied to one or more companion devices, such as in a device constellation arrangement. One or more of these devices may access the network together and / or individually.

[0060] Refer again Figure 1 In some aspects, UE 104 may have a visual-assisted positioning component 198, which may be configured to: receive a list of visual features and the location of each visual feature in the list from a reference device, server, or map; identify at least one visual feature in an area via at least one camera, wherein the at least one visual feature is included in the list of visual features, wherein the area is within a threshold distance of the UE; and estimate the UE's location based on the identified at least one visual feature in the area and the location corresponding to the at least one visual feature. In some aspects, a reference system / device (e.g., reference system 904), base station 102, or one or more location servers 168 may have a reference information generation component 199, which may be configured to: estimate the six degrees of freedom (6DOF) of the reference device, and transmit the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and a set of Global Navigation Satellite System (GNSS) measurements.

[0061] Figure 2A Figure 200 illustrates an example of the first subframe within a 5G NR frame structure. Figure 2B Figure 230 illustrates an example of a DL channel within a 5G NR subframe. Figure 2C Figure 250 is an example of a second subframe within a 5G NR frame structure. Figure 2DFigure 280 illustrates an example of a UL channel within a 5G NR subframe. The 5G NR frame structure can be Frequency Division Duplex (FDD) (where subframes within a specific set of subcarriers (carrier system bandwidth) are dedicated to either DL or UL) or Time Division Duplex (TDD) (where subframes within a specific set of subcarriers (carrier system bandwidth) are dedicated to both DL and UL). Figure 2A , Figure 2C In the provided example, the 5G NR frame structure is assumed to be TDD, where subframe 4 is configured with slot format 28 (most of which are DL), where D is DL, U is UL, and F is flexible between DL / UL, and subframe 3 is configured with slot format 1 (all of which are UL). Although subframes 3 and 4 are shown as having slot formats 1 and 28 respectively, any particular subframe can be configured with any of the various available slot formats 0-61. Slot formats 0 and 1 are both DL and UL, respectively. Other slot formats 2-61 include a mixture of DL, UL, and flexible symbols. The slot format is configured for the UE via the received Slot Format Indicator (SFI) (dynamically configured via DL Control Information (DCI) or semi-statically / statically configured via Radio Resource Control (RRC) signaling). Note that the following description also applies to the 5G NR frame structure as TDD.

[0062] Figures 2A to 2D The frame structure is illustrated, and aspects of this disclosure are applicable to other wireless communication technologies that may have different frame structures and / or different channels. A frame (10 ms) can be divided into 10 equal-sized subframes (1 ms). Each subframe may include one or more time slots. Subframes may also include micro-time slots, which may include 7, 4, or 2 symbols. Each time slot may include 14 or 12 symbols, depending on whether the cyclic prefix (CP) is normal or extended. For normal CP, each time slot may include 14 symbols, and for extended CP, each time slot may include 12 symbols. Symbols on the DL may be CP Orthogonal Frequency Division Multiplexing (OFDM) (CP-OFDM) symbols. Symbols on the UL may be CP-OFDM symbols (for high-throughput scenarios) or Discrete Fourier Transform (DFT) Extended OFDM (DFT-s-OFDM) symbols (for power-constrained scenarios; limited to single-stream transmission). The number of time slots within a subframe is based on the CP and a parameter set. The parameter set defines the subcarrier spacing (SCS) (see Table 1). Symbol length / duration can be scaled with 1 / SCS.

[0063] Table 1: Parameter Set, SCS, and CP For a normal CP (14 symbols / slot), different parameter sets µ 0 through 4 allow 1, 2, 4, 8, and 16 slots per subframe, respectively. For an extended CP, parameter set 2 allows 4 slots per subframe. Therefore, for a normal CP and parameter set µ, there are 14 symbols / slot and 2... µ One time slot / subframe. Subcarrier spacing can be equal to ,in The parameter sets are 0 to 4. Therefore, the subcarrier spacing is 15 kHz for parameter set µ=0 and 240 kHz for parameter set µ=4. The symbol length / duration is negatively correlated with the subcarrier spacing. Figures 2A to 2D Examples of a normal frequency division multiplexing (CP) with 14 symbols per time slot and a parameter set of µ=2 with 4 time slots per subframe are provided. The time slot duration is 0.25 ms, the subcarrier spacing is 60 kHz, and the symbol duration is approximately 16.67 μs. Within the frame set, there may be one or more distinct bandwidth portions (BWPs) of frequency division multiplexing (see [link to relevant documentation]). Figure 2B Each BWP can have a specific set of parameters and CP (normal or extended).

[0064] A resource grid can be used to represent the frame structure. Each time slot consists of a resource block (RB) extending for 12 consecutive subcarriers (also known as a physical RB (PRB)). The resource grid is divided into multiple resource elements (REs). The number of bits carried by each RE depends on the modulation scheme.

[0065] like Figure 2A As illustrated, some of the REs carry reference (pilot) signals (RS) for the UE. RS may include demodulation RS (DM-RS) (indicated as R for a particular configuration, but other DM-RS configurations are possible) and channel state information reference signals (CSI-RS) for channel estimation at the UE. RS may also include beam measurement RS (BRS), beam refinement RS (BRRS), and phase tracking RS (PT-RS).

[0066] Figure 2BExamples of various DL channels within a subframe of a frame are illustrated. The Physical Downlink Control Channel (PDCCH) carries the DCI within one or more Control Channel Elements (CCEs) (e.g., 1, 2, 4, 8, or 16 CCEs), each CCE comprising six RE Groups (REGs), each REG comprising 12 consecutive REs in the OFDM symbol of the RB. A PDCCH within a BWP can be referred to as a Control Resource Set (CORESET). The UE is configured to monitor PDCCH candidates in the PDCCH search space (e.g., the common search space, the UE-specific search space) during PDCCH monitoring timing on the CORESET, where the PDCCH candidates have different DCI formats and different aggregation levels. Additional BWPs may be located at higher and / or lower frequencies on the channel bandwidth. The Primary Synchronization Signal (PSS) may be located within symbol 2 of a specific subframe of the frame. The PSS is used by the UE 104 to determine subframe / symbol timing and physical layer identification. The Secondary Synchronization Signal (SSS) may be located within symbol 4 of a specific subframe of the frame. The SSS is used by the UE to determine the Physical Layer Cell Identifier Group Number and radio frame timing. Based on the Physical Layer Identifier and the Physical Layer Cell Identifier Group Number, the UE can determine the Physical Cell Identifier (PCI). Based on the PCI, the UE can determine the location of the DM-RS. The Physical Broadcast Channel (PBCH), carrying the Master Information Block (MIB), can be logically grouped with the PSS and SSS to form a Synchronization Signal (SS) / PBCH block (also known as an SS block (SSB)). The MIB provides the System Frame Number (SFN) and the number of Restricted Blocks (RBs) in the system bandwidth. The Physical Downlink Shared Channel (PDSCH) carries user data, broadcast system information not transmitted via the PBCH (such as System Information Blocks (SIBs)), and paging messages.

[0067] like Figure 2C As illustrated, some REs in the REs carry DM-RS (indicated as R for one particular configuration, but other DM-RS configurations are possible) for channel estimation at the base station. The UE can transmit DM-RS for the Physical Uplink Control Channel (PUCCH) and DM-RS for the Physical Uplink Shared Channel (PUSCH). The PUSCH DM-RS can be transmitted in the first or first two symbols of the PUSCH. Depending on whether a short or long PUCCH is transmitted and depending on the specific PUCCH format used, the PUCCH DM-RS can be transmitted in different configurations. The UE can transmit a Sounding Reference Signal (SRS). The SRS can be transmitted in the last symbol of a subframe. The SRS can have a comb structure, and the UE can transmit the SRS on one of the comb teeth. The SRS can be used by the base station for channel quality estimation to enable frequency-dependent scheduling of the UL.

[0068] Figure 2DExamples of various UL channels within a subframe of a frame are illustrated. The PUCCH may be located as indicated in one configuration. The PUCCH carries uplink control information (UCI), such as scheduling requests, channel quality indicators (CQI), pre-decoding matrix indicators (PMI), rank indicators (RI), and hybrid automatic repeat request (HARQ) acknowledgment (ACK) (HARQ-ACK) feedback (i.e., one or more HARQ ACK bits indicating one or more ACKs and / or negative ACKs (NACKs)). The PUCCH carries data and may additionally be used to carry buffer status reports (BSR), power clearance reports (PHR), and / or UCIs.

[0069] Figure 3 This is a block diagram illustrating communication between base station 310 and UE 350 in the access network. In the DL, Internet Protocol (IP) packets can be provided to controller / processor 375. Controller / processor 375 implements Layer 3 and Layer 2 functionality. Layer 3 includes the Radio Resource Control (RRC) layer, and Layer 2 includes the Service Data Adaptation Protocol (SDAP) layer, Packet Data Convergence Protocol (PDCP) layer, Radio Link Control (RLC) layer, and Media Access Control (MAC) layer. The controller / processor 375 provides RRC layer functionality associated with broadcasting system information (e.g., MIB, SIB), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter-Radio Access Technology (RAT) mobility, and measurement configuration for UE measurement reporting; PDCP layer functionality associated with header compression / decompression, security (encryption, decryption, integrity protection, integrity verification), and handover support functions; RLC layer functionality associated with the delivery of upper-layer packet data units (PDUs), error correction via ARQ, concatenation, segmentation, and reassembly of RLC service data units (SDUs), resegmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction via HARQ, priority handling, and logical channel priority ordering.

[0070] Transmit (TX) processor 316 and receive (RX) processor 370 implement Layer 1 functionality associated with various signal processing functions. Layer 1 (which includes the physical (PHY) layer) may include error detection on the transport channel, forward error correction (FEC) decoding / decoding of the transport channel, interleaving, rate matching, mapping to the physical channel, modulation / demodulation of the physical channel, and MIMO antenna processing. TX processor 316 processes the mapping to the signal constellation based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-order phase shift keying (M-PSK), M-order quadrature amplitude modulation (M-QAM)). The decoded and modulated symbols can then be split into parallel streams. Each stream can then be mapped to OFDM subcarriers, multiplexed with a reference signal (e.g., a pilot) in the time and / or frequency domains, and subsequently combined using inverse fast Fourier transform (IFFT) to produce a physical channel carrying a stream of time-domain OFDM symbols. The OFDM stream is spatially pre-decoded to generate multiple spatial streams. Channel estimates from channel estimator 374 can be used to determine the decoding and modulation scheme, as well as for spatial processing. Channel estimates can be derived from reference signals transmitted by UE 350 and / or channel condition feedback. Each spatial stream can then be provided to different antennas 320 via a separate transmitter 318Tx. Each transmitter 318Tx can use the corresponding spatial stream to modulate a radio frequency (RF) carrier for transmission.

[0071] At UE 350, each receiver 354Rx receives signals via its corresponding antenna 352. Each receiver 354Rx recovers the information modulated onto the RF carrier and provides that information to the receive (RX) processor 356. The TX processor 368 and RX processor 356 implement Layer 1 functionality associated with various signal processing functions. The RX processor 356 can perform spatial processing on the information to recover any spatial stream destined for UE 350. If multiple spatial streams are destined for UE 350, the RX processor 356 can combine them into a single OFDM symbol stream. The RX processor 356 then uses a Fast Fourier Transform (FFT) to transform the OFDM symbol stream from the time domain to the frequency domain. The frequency domain signal consists of a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbols on each subcarrier, along with the reference signal, are recovered and demodulated by determining the most probable signal constellation point transmitted by base station 310. These soft decisions can be based on a channel estimate calculated by channel estimator 358. Subsequently, the soft decision is decoded and deinterleaved to recover the data and control signals originally transmitted by base station 310 on the physical channel. The data and control signals are then provided to controller / processor 359, which implements layer 3 and layer 2 functionality.

[0072] The controller / processor 359 may be associated with at least one memory 360 storing program code and data. The at least one memory 360 may be referred to as a computer-readable medium. In the UL, the controller / processor 359 provides demultiplexing, packet reassembly, decryption, header decompression, and control signal processing between transport and logical channels to recover IP packets. The controller / processor 359 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0073] Similar to the functionality described in conjunction with DL transmission performed by base station 310, controller / processor 359 provides RRC layer functionality associated with system information (e.g., MIB, SIB) acquisition, RRC connectivity, and measurement reporting; PDCP layer functionality associated with header compression / decompression and security (encryption, decryption, integrity protection, integrity verification); RLC layer functionality associated with upper-layer PDU delivery, error correction via ARQ, concatenation, segmentation and reassembly of RLC SDUs, resegmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto TBs, demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction via HARQ, priority handling, and logical channel priority ordering.

[0074] The TX processor 368 can use the channel estimate derived from the reference signal or feedback transmitted by the channel estimator 358 from the base station 310 to select an appropriate decoding and modulation scheme and facilitate spatial processing. The spatial stream generated by the TX processor 368 can be provided to different antennas 352 via individual transmitters 354Tx. Each transmitter 354Tx can use the corresponding spatial stream to modulate an RF carrier for transmission.

[0075] UL transmission is processed at base station 310 in a manner similar to that described in conjunction with the receiver function at UE 350. Each receiver 318Rx receives signals via its corresponding antenna 320. Each receiver 318Rx recovers the information modulated onto the RF carrier and provides that information to RX processor 370.

[0076] The controller / processor 375 may be associated with at least one memory 376 storing program code and data. The at least one memory 376 may be referred to as a computer-readable medium. In the UL, the controller / processor 375 provides demultiplexing, packet reassembly, decryption, header decompression, and control signal processing to recover IP packets between transport and logical channels. The controller / processor 375 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0077] At least one of the TX processor 368, RX processor 356, and controller / processor 359 can be configured to combine Figure 1 The visual-assisted positioning component 198 performs various functions.

[0078] At least one of the TX processor 316, RX processor 370, and controller / processor 375 can be configured to combine Figure 1 The reference information generation component 199 is used to perform various aspects.

[0079] Figure 4 Figure 400 illustrates an example of UE positioning (which may also be referred to as "network-based positioning") based on reference signal measurements according to various aspects of this disclosure. UE 404 can [operate at time T]. SRS_TX Send UL-SRS 412 and at time T PRS_RX Receives the DL positioning reference signal (PRS) (DL-PRS) 410. TRP 406 can be used at time T. SRS_RX Receive UL-SRS 412 and at time T PRS_TX Send DL-PRS 410. UE 404 may receive DL-PRS 410 before sending UL-SRS 412, or may send UL-SRS 412 before receiving DL-PRS 410. In both cases, the location server (e.g., location server 168) or UE 404 may base its response on ||T SRS_RX – T PRS_TX | – |T SRS_TX – T PRS_RX || to determine RTT 414. Therefore, multi-RTT positioning can utilize the UE Rx-Tx time difference measurement (i.e., |T) of downlink signals received from multiple TRPs 402, 406 and measured by UE 404. SRS_TX – T PRS_RX |) and DL PRS reference signal received power (RSRP) (DL PRS-RSRP), and the measured TRP Rx-Tx time difference (i.e., |T) of the uplink signal transmitted from UE 404 at multiple TRPs 402, 406. SRS_RX –T PRS_TX|) and UL SRS-RSRP. UE 404 uses auxiliary data received from the positioning server to measure the UE Rx-Tx time difference (and / or the DL-PRS-RSRP of the received signal), and TRPs 402, 406 use auxiliary data received from the positioning server to measure the gNB Rx-Tx time difference (and / or the UL-SRS-RSRP of the received signal). These measurements can be used at the positioning server or at UE 404 to determine the RTT, which is used to estimate the location of UE 404. Other methods for determining the RTT are possible, such as, for example, using DL-TDOA and / or UL-TDOA measurements.

[0080] PRS can be defined for network-based positioning (e.g., NR positioning) to enable the UE to detect and measure more neighboring transmit and receive points (TRPs), supporting various configurations for diverse deployments (e.g., indoor, outdoor, sub-6, mmW, etc.). Beam scanning can also be configured for PRS to support PRS beam operation. The UL positioning reference signal can be based on an enhanced / adjusted probe reference signal (SRS) for positioning purposes. In some examples, the UL-PRS may be referred to as "SRS for Positioning," and new information elements (IEs) can be configured for the SRS for positioning in RRC signaling.

[0081] DL PRS-RSRP can be defined as the linear average of the power contribution (in [W]) of a resource element carrying a DL PRS reference signal configured for RSRP measurement at an antenna port within the considered measurement frequency bandwidth. In some examples, for FR1, the reference point for DL ​​PRS-RSRP can be the UE's antenna connector. For FR2, DL PRS-RSRP can be measured based on a combined signal from an antenna element corresponding to a given receiver branch. For FR1 and FR2, if the UE uses receiver diversity, the reported DL PRS-RSRP value can be no less than the corresponding DL PRS-RSRP of any individual receiver branch within the individual receiver branch. Similarly, UL SRS-RSRP can be defined as the linear average of the power contribution (in [W]) of a resource element carrying a probe reference signal (SRS). UL SRS-RSRP can be measured by a configured resource element within the considered measurement frequency bandwidth at a configured measurement time. In some examples, for FR1, the reference point for UL SRS-RSRP can be the antenna connector of a base station (e.g., gNB). For FR2, the UL SRS-RSRP can be measured based on the combined signal from the antenna element corresponding to a given receiver branch. For FR1 and FR2, if the base station uses receiver diversity, the reported UL SRS-RSRP value may not be lower than the corresponding UL SRS-RSRP of any individual receiver branch within the individual receiver branch.

[0082] PRS-Path RSRP (PRS-RSRPP) can be defined as the power of the linear average of the channel response at the i-th path delay carrying the resource element configured for measurement of the DL PRS signal, where the DL PRS-RSRPP at the first path delay is the power contribution corresponding to the first detected path in time. In some examples, the PRS path phase measurement may refer to the phase associated with the i-th path of the channel derived using the PRS resource.

[0083] DL-AoD positioning utilizes the measured DL-PRS-RSRP of downlink signals received at UE 404 from multiple TRPs 402, 406. UE 404 uses auxiliary data received from the positioning server to measure the DL-PRS-RSRP of the received signals, and the resulting measurement, along with the azimuth departure (A-AoD), zenith departure (Z-AoD), and other configuration information, is used to position UE 404 relative to adjacent TRPs 402, 406.

[0084] DL-TDOA positioning utilizes the DL Reference Signal Time Difference (RSTD) (and / or DL-PRS-RSRP) of downlink signals received at UE 404 from multiple TRPs 402, 406. UE 404 uses auxiliary data received from the positioning server to measure the DL RSTD (and / or DL-PRS-RSRP) of the received signals, and the resulting measurement, along with other configuration information, is used to position UE 404 relative to adjacent TRPs 402, 406.

[0085] UL-TDOA positioning utilizes the UL relative time of arrival (RTOA) (and / or UL-SRS-RSRP) of the uplink signal transmitted from UE 404 at multiple TRPs 402, 406. TRPs 402, 406 use auxiliary data received from the positioning server to measure the UL-RTOA (and / or UL-SRS-RSRP) of the received signal, and the resulting measurements, along with other configuration information, are used to estimate the location of UE 404.

[0086] UL-AoA positioning utilizes the azimuth angle (A-AoA) and zenith angle (Z-AoA) of the uplink signal transmitted from UE 404 at multiple TRPs 402, 406. TRPs 402, 406 use auxiliary data received from a positioning server to measure the A-AoA and Z-AoA of the received signal, and the resulting measurements, along with other configuration information, are used to estimate the position of UE 404. For the purposes of this disclosure, a positioning operation in which the UE provides measurements to a base station / positioning entity / server for calculating the UE's position can be described as "UE-assisted," "UE-assisted positioning," and / or "UE-assisted position calculation," while a positioning operation in which the UE measures and calculates its own position can be described as "UE-based," "UE-based positioning," and / or "UE-based position calculation."

[0087] Additional positioning methods can be used to estimate the location of UE 404, such as, for example, UE-side UL-AoD and / or DL-AoA. It should be noted that data / measurements from various technologies can be combined in various ways to increase accuracy, determine and / or enhance certainty, supplement / improve measurements, and / or replace / provide missing information.

[0088] It should be noted that the terms "location reference signal" and "PRS" generally refer to specific reference signals used for positioning in NR and LTE systems. However, as used herein, the terms "location reference signal" and "PRS" can also refer to any type of reference signal that can be used for positioning, such as, but not limited to, PRS, TRS, PTRS, CRS, CSI-RS, DMRS, PSS, SSS, SSB, SRS, UL-PRS, etc., as defined in LTE and NR. Furthermore, the terms "location reference signal" and "PRS" can refer to downlink or uplink positioning reference signals, unless otherwise indicated by the context. To further distinguish the types of PRS, downlink positioning reference signals may be referred to as "DL PRS," and uplink positioning reference signals (e.g., SRS, PTRS used for positioning) may be referred to as "UL-PRS." Additionally, for signals that can be transmitted in both uplink and downlink (e.g., DMRS, PTRS), these signals may be prefixed with "UL" or "DL" to distinguish direction. For example, "UL-DMRS" can be distinguished from "DL-DMRS." Furthermore, the terms “location” and “positioning” are used interchangeably throughout the specification, and the term can refer to a specific geographical location or a relative location.

[0089] A device (e.g., a UE) equipped with a Global Navigation Satellite System (GNSS) receiver (which may include a Global Positioning System (GPS) receiver) can determine its location based on GNSS positioning. GNSS is a satellite network that broadcasts timing and orbital information for navigation and positioning measurements. GNSS may include multiple groups of satellites, referred to as constellations, that broadcast signals (which may be referred to as GNSS signals) to GNSS control stations and users. Based on the broadcast signals, users may be able to determine their location (e.g., via a trilateration process). For the purposes of this disclosure, a device equipped with a GNSS receiver or capable of receiving GNSS signals (e.g., a UE) may be referred to as a GNSS device, and a device capable of transmitting GNSS signals (such as a satellite) may be referred to as a space vehicle (SV).

[0090] Figure 5Figure 500 illustrates examples of GNSS positioning according to various aspects of this disclosure. A GNSS device 506 may estimate its position and time based at least in part on data (e.g., GNSS signals 504) received from multiple space vehicles (SVs) 502, wherein each SV 502 may carry a record of its position and time and may transmit such data (e.g., the record) to the GNSS device 506. Each SV 502 may also include a clock synchronized with the other clocks of the SV and with a ground clock. If an SV 502 detects a deviation from the time maintained on the ground, the SV 502 may correct for it. The GNSS device 506 may also include a clock, but the clock of the GNSS device 506 may be less stable and accurate compared to the clocks of each SV 502.

[0091] Since the speed of radio waves can be constant and independent of satellite speed, the time delay between the time SV 502 transmits GNSS signal 504 and the time GNSS device 506 receives GNSS signal 504 can be proportional to the distance from SV 502 to GNSS device 506. In some examples, GNSS device 506 can use at least four SVs to calculate / estimate one or more unknowns associated with positioning (e.g., three positioning coordinates and clock offset from satellite time, etc.).

[0092] Each SV 502 can continuously broadcast a GNSS signal 504 (e.g., a modulated carrier wave), which may include a pseudo-random code known to the GNSS device 506 (e.g., a sequence of one and zero), and may also include a message including the transmission time and the SV's location at that time. In other words, each GNSS signal 504 can carry two types of information: time and carrier wave (e.g., a modulated waveform of an input signal to be transmitted electromagnetically). Based on the GNSS signal 504 received from each SV 502, the GNSS device 506 can measure the time of arrival (TOA) of the GNSS signal 504 and calculate the time of flight (TOF) of the GNSS signal 504. Then, based on the TOF, the GNSS device 506 can calculate its three-dimensional location and clock offset, and the GNSS device 506 can determine its location on Earth. For example, the location of the GNSS device 506 can be converted into latitude, longitude, and altitude relative to an ellipsoidal Earth model. These coordinates can be displayed on a mobile map display, or recorded or used by other systems such as vehicle guidance systems.

[0093] While the distance between the GNSS device and the SV can be estimated based on the time it takes for the GNSS signal to reach the GNSS device, the SV's signal sequence may be delayed relative to the GNSS device's sequence. Therefore, in some examples, a delay can be applied to the GNSS device's sequence to align the two sequences. For instance, to estimate the delay, the GNSS device can align the pseudo-random binary sequence included in the SV signal with an internally generated pseudo-random binary sequence. Because the SV's GNSS signal takes time to reach the GNSS device, the SV's sequence may be delayed relative to the GNSS device's sequence. By gradually delaying the GNSS device's sequence, the two sequences can eventually be aligned.

[0094] The accuracy of GNSS-based positioning can depend on various factors, such as satellite geometry, signal obstruction, atmospheric conditions, and / or receiver design characteristics / quality. For example, a GNSS receiver used by a smartphone or smartwatch may have lower accuracy compared to a GNSS receiver used by a vehicle or exploration equipment. To improve the accuracy of GNSS positioning (e.g., from meters to centimeters), real-time kinematics (RTK) techniques or mechanisms (hereinafter collectively referred to as RTK engines) can be used in positioning devices (e.g., UEs, surveying equipment, automotive GNSS systems, etc.). For example, an RTK engine enables positioning devices to use correction information from base stations to mitigate one or more error sources in GNSS receiver pseudorange (PR) and carrier phase (CP) measurements, which may include satellite orbit errors, satellite clock errors, and / or atmospheric errors. Therefore, the positioning device can achieve better accuracy.

[0095] Figure 6 Figure 600 illustrates examples of RTK positioning according to various aspects of this disclosure. In one example, at least two receivers may be used in association with RTK positioning, wherein at least one of the receivers may be fixed, which may be referred to as base station 602 or RTK base station, and at least one other receiver may be mobile (e.g., may move from time to time), which may be referred to as rover or rover device 604 (e.g., GNSS / GPS receiver, UE, rover, etc.). In other words, an RTK system may include at least a base station and a rover, wherein the base station may be a fixed receiver with a known location.

[0096] The range between SV 606 (e.g., a GNSS / GPS satellite) and rover equipment 604, or between SV 606 and base station 602, can be calculated by determining the number of carrier cycles between SV 606 and rover equipment 604 or base station 602 and multiplying that number by the carrier wavelength 612 of the carrier 610 (e.g., a carrier signal) transmitted by SV 606. For example, if SV 606 transmits a carrier 610 with a carrier wavelength 612 of ten (10) meters, and rover equipment 604 receives the carrier 610 and determines that there are five hundred (500) carrier cycles between SV 606 and rover equipment 604, then rover equipment 604 can calculate the distance between SV 606 and rover equipment 604 by multiplying the determined number of carrier cycles (e.g., 500) by the carrier wavelength 612 (e.g., 10 meters), which could be five kilometers (e.g., 500 × 10 = 5000). Similarly, base station 602 can also receive carrier 610 from SV 606 and determine the range of the carrier from satellite 606 based on the carrier wavelength 612 of carrier 610 and the number of carrier cycles between base station 602 and SV 606. Rover equipment 604 and / or base station 602 can calculate the range (e.g., distance) between rover equipment 604 / base station 602 and multiple (e.g., four or more) SVs (e.g., SV 606 and SV 608) to determine their geographic locations (e.g., their positions on Earth).

[0097] During RTK positioning, rover device 604 (e.g., UE, client device, etc.) may undergo an "ambiguity resolution" process to determine the number of carrier cycles between SV 606 and rover device 604. In other words, when rover device 604 receives a carrier from SV 606, it may spend time calculating how many carrier cycles exist between SV 606 and rover device 604. In some examples, a GNSS receiver with more complex or high-end antennas / hardware (such as automotive-grade antennas) may be able to resolve ambiguities in a relatively short time (e.g., within seconds), while a GNSS receiver with less complex or low-end antennas / hardware (such as antennas for mobile phones and / or smartwatches) may take longer (e.g., 10 to 30 minutes or more) to resolve ambiguities. In some examples, the ambiguity may also be referred to as "integer ambiguity." In some examples, the process of GNSS receiver resolving ambiguities may be referred to as convergence, and the time spent by the device resolving ambiguities may be referred to as the convergence time.

[0098] In some scenarios, the range calculated by rover device 604 may include errors due to SV clock and ephemeris, as well as ionospheric and tropospheric delays. Furthermore, since rover device 604 is more likely to be mobile, the quality of the signal / carrier received from each SV may change as the rover device moves from one location to another. For example, if rover device 604 moves from an open-sky area to an area with buildings, signals from one or more SVs 606 / 608 may be blocked / reflected by buildings. Therefore, the range calculated by rover device 604 may begin to drift and may include errors.

[0099] On the other hand, since base station 602 is likely fixed with a known location, and base station 602 may be equipped with a more sophisticated and advanced GNSS receiver, base station 602 may be able to maintain accurate range calculations compared to rover equipment 604. For example, base station 602 may be located at a site with minimal environmental impacts (such as interference and multipath) (e.g., an open-sky area). Thus, under RTK positioning, since base station 602 may already know its location (e.g., via predicted quantities), base station 602 can perform measurements on the SV to obtain a reference receiver measurement (e.g., to estimate the difference between the base station and the SV). Base station 602 can then subtract the geometric distance between the base station location and the SV location from this reference receiver measurement to obtain a reference correction (e.g., based on the difference or error). Base station 602 can generate correction data 614 (or a correction signal) based on the obtained reference correction and send the correction data 614 to rover equipment 604 to help rover equipment 604 correct for errors. For example, since rover device 604 is typically configured to be located near base station 602 (e.g., within 6 miles, 12 miles, etc.), rover device 604 is likely to encounter similar errors to base station 602 (e.g., similar ionospheric and tropospheric delays, etc.). Therefore, rover device 604 can use correction data 614 from base station 602 to improve and speed up its own positioning calculated from the GNSS constellation to achieve centimeter accuracy. In other words, the base station can be configured to remain in a fixed / known location and transmit correction data to one or more rover devices, and one or more rover devices can use the correction data to increase the accuracy of their positioning and the speed of error correction. Therefore, rover device 604 can use an algorithm combining ambiguity resolution and differential correction to determine its positioning. The positioning accuracy achievable by rover device 604 may depend on its distance from base station 602 and the accuracy of differential correction (e.g., correction data 614).

[0100] In addition to positioning based on the Global Navigation Satellite System (GNSS) (e.g., combined with...) Figure 5 (as described) and network-based positioning (e.g., as combined with) Figure 4In addition to those described, various camera-based localization methods have been developed to provide alternative / additional localization mechanisms / modes. Camera-based localization (which may also be referred to as "camera-based visual localization," "visual localization," and / or "vision-based localization") is a localization mechanism / mode that uses images captured by at least one camera to determine the location of a target (e.g., a UE or vehicle equipped with at least one camera, an object in the field of view (FOV) of at least one camera, etc.). For example, when a vehicle is moving, an image captured by the vehicle's dashboard camera can be used to calculate the vehicle's three-dimensional (3D) localization and / or 3D orientation. Similarly, an image captured by a camera of a mobile device can be used to estimate the location of the mobile device or the location of one or more objects in an image. In another example, a camera (or UE) can determine its localization by matching objects in an image captured by the camera (or UE) with objects in a map (e.g., a high-definition (HD) map), such as designated buildings, landmarks, road / street signs, etc. In some specific implementations, camera-based localization can provide centimeter-level and 6-DOF localization. 6DOF can refer to a representation of how an object moves through 3D space via linear translation or axial rotation (e.g., 6DOF = 3D positioning + 3D attitude). For example, a single degree of freedom on an object can be controlled by up / down, forward / backward, left / right, pitch, roll, or yaw. Camera-based positioning has great potential for a variety of applications, such as in environments where satellite signals (e.g., GNSS / GPS signals) are degraded / unavailable.

[0101] In some scenarios, camera-captured images can also be used to improve the accuracy / reliability of other positioning mechanisms / modes (e.g., GNSS-based positioning, network-based positioning, etc.), which may be referred to as "visual-assisted positioning," "visual-assisted precise positioning (VAPP)," "camera-assisted positioning," "camera-assisted location," and / or "camera-assisted perception," etc. For example, positioning techniques using GNSS and inertial measurement unit (IMU) coupling can achieve highly accurate location solutions. However, when GNSS measurement is interrupted (e.g., GNSS signals are unavailable or weak), IMU bias drift can reduce positioning accuracy. This IMU bias can also cause initial sensor alignment and / or heading ambiguity during static startup. In other words, while GNSS and / or IMU can provide good position determination / positioning performance, overall positioning performance can be degraded due to IMU bias drift when GNSS measurement is interrupted. Opportunistic use of camera vision can leverage useful and reliable visual features to mitigate the challenges faced by GNSS and IMU GNSS coupling solutions. For example, camera-captured images can provide valuable information to reduce errors. For the purposes of this disclosure, a positioning session associated with camera-based positioning or camera-assisted positioning (e.g., a time period in which one or more entities are configured to determine the location of a UE or a target) may be referred to as a camera-based positioning session or a camera-assisted positioning session. In some examples, camera-based positioning and / or camera-assisted positioning may be associated with the absolute location of the UE, the relative location of the UE, the orientation of the UE, or a combination thereof.

[0102] Figure 7 Figure 700 illustrates examples of camera-assisted positioning according to various aspects of this disclosure. A vehicle 702 may be equipped with a GNSS system and a set of cameras, which may include a front camera 704 (for capturing a front view of the vehicle 702), a side camera 706 (for capturing a side view of the vehicle 702), and / or a rear camera 708 (for capturing a rear view of the vehicle 702), etc. In some examples, the GNSS system may also include or be associated with at least one IMU (which may be referred to as a "GNSS+IMU system"). Although Figure 7 Vehicle 702 is used as an example, but it is for illustrative purposes only. The various aspects presented herein can also be applied to other types of transportation (e.g., motorcycles, bicycles, buses, trains, etc.), devices (e.g., UEs on pedestrians), and / or positioning mechanisms / modes (e.g., combined with...). Figure 4 (The described network-based positioning). Furthermore, for the purposes of this disclosure, a positioning mechanism / mode that uses at least one sensor (e.g., IMU, camera, etc.) to assist in positioning (e.g., GNSS-based positioning, network-based positioning, etc.) may be referred to as sensor fusion positioning.

[0103] A GNSS system can be used to estimate the position of vehicle 702 based on receiving GNSS signals transmitted from multiple satellites (e.g., based on performing GNSS-based positioning). However, when GNSS signals are unavailable or weak (this may be referred to as a GNSS outage), such as when vehicle 702 is in an urban area or tunnel, the estimated position of vehicle 702 may become inaccurate. Therefore, in some specific implementations, the set of cameras on vehicle 702 can be used to assist positioning, such as to verify whether the position estimated by the GNSS system based on GNSS signals is accurate. For example, as shown at 710, the image captured by the front-facing camera 704 of vehicle 702 may include / identify a specific building 712 with a known location (which may also be referred to as a feature), and vehicle 702 (or the GNSS system or the positioning engine associated with vehicle 702) can determine / verify whether the position estimated by the GNSS system (e.g., longitude and latitude coordinates) is close to the known location of that specific building 712. Therefore, with the assistance of cameras, the accuracy and reliability of GNSS-based positioning can be further improved. For the purposes of this disclosure, a GNSS system associated with a camera (e.g., capable of performing camera-assisted / camera-based positioning) may be referred to as a "GNSS+camera system," or (if the GNSS system is also associated with / includes at least one IMU) as a "GNSS+IMU+camera system." A vision-assisted positioning mechanism capable of achieving advanced positioning accuracy (e.g., meeting defined accuracy thresholds) may be referred to as vision-assisted precise positioning (VAPP).

[0104] In some examples, software or applications that accept positioning-related measurements from GNSS chipsets, sensors, and / or cameras to estimate the location, velocity, and / or altitude of a device (or target) can be referred to as a positioning engine (PE). Similarly, a positioning engine capable of achieving a high level of accuracy (e.g., centimeter / decimeter accuracy) and / or latency can be referred to as a precision positioning engine (PPE). For example, an engine capable of performing real-time motion positioning (RTK) (e.g., receiving or processing correction data associated with RTK, such as combining...) Figure 6 The positioning engine described herein can be considered a PPE. Another example of a PPE is a positioning engine capable of performing Precise Point Positioning (PPP). PPP is a positioning technique that removes GNSS system errors or models those errors to provide a high level of positioning accuracy from a single receiver.

[0105] In some examples, navigation applications / software can refer to applications within user equipment (e.g., smartphones, in-vehicle navigation systems, GPS devices, etc.) that provide real-time navigation guidance. Over the past few years, users have become increasingly reliant on navigation applications due to the various benefits they offer. For example, navigation applications facilitate users by enabling them to find routes to their destinations and allow users to contribute information and mark important locations, thus generating the most accurate description of a location. In some examples, navigation applications can also provide specialized guidance, directing users to their destinations via the best, most direct, or most time-efficient routes. For instance, a navigation application can obtain the current traffic status and then locate the shortest and fastest route to the user's destination, providing approximately how long it will take to reach the destination. Therefore, navigation applications can use internet connectivity and GPS / GNSS navigation systems to provide turn-by-turn guidance instructions on how to reach a given destination.

[0106] Figure 8 Figure 800 illustrates examples of navigation applications according to various aspects of this disclosure. As shown at 802, a navigation application running on a UE (such as a vehicle (e.g., a vehicle's built-in GPS / GNSS system) or a smartphone) can provide a user (e.g., via a display or interface) with turn-by-turn directions to a destination and an estimated time of arrival based on real-time information. For example, the navigation application may receive / download real-time traffic information, road condition information, local traffic rules (e.g., speed limits), and / or map information / data from a server. The navigation application can then calculate a route to the destination based at least on the map information and other available information. The map information may include a map of the area in which the user is traveling, such as the area's streets, buildings, and / or terrain, or a map compatible with the navigation application and the GPS / GNSS system. In some examples, the route calculated by the navigation application may be the shortest or fastest route. For the purposes of this disclosure, the information associated with the calculated route may be referred to as navigation route information. For example, navigation route information may include the user's predicted / estimated location, speed, acceleration, direction, and / or altitude at different points in time.

[0107] For example, as shown at 804, based on map information, speed limits, and real-time road condition information, a navigation application can generate navigation route information 806 to guide user 808 to their destination. In some examples, the navigation route information 806 may include the user's location and the user's speed relative to / with respect to time, which may be denoted as... and For example, a navigation application can estimate that at a first time point (T1), a user can reach a first point / location at a specific speed (e.g., at the intersection of 59th Street and Vista Drive at 35 mph), and at a second time point (T2), a user can reach a second point / location at a specific speed (e.g., at the intersection of 80th Street and Vista Drive at 15 mph), and so on up to the Nth time point (TN), and so on.

[0108] In recent years, vehicle manufacturers have developed vehicles with autonomous driving capabilities. Autonomous driving (also known as self-driving or driverless technology) refers to the ability of a vehicle to navigate and operate itself without designated human intervention (e.g., without a person controlling the vehicle). The goal of autonomous driving is to create vehicles capable of perceiving their surroundings, making decisions, and controlling their movement, all without the direct involvement of a human driver.

[0109] To enable or improve autonomous driving, vehicles may be required to use maps (or map data) with detailed information, such as high-definition (HD) maps. HD maps can refer to highly detailed and accurate digital maps designed for autonomous driving and advanced driver assistance systems (ADAS). In one example, an HD map may typically include one or more of the following: (1) geometric information (e.g., precise road geometry, including detailed 3D models of lane boundaries, curvature, slope, and surrounding environment); (2) lane-level information (e.g., information about individual lanes on the road, such as lane width, lane type (e.g., driving, turning, or parking lanes), and lane connectivity); (3) road attributes (e.g., data about road features such as traffic signs, signals, traffic lights, speed limits, and road markings); (4) topology (e.g., information about relationships between different roads, intersections, and connectivity patterns); (5) static objects (e.g., the location and details of fixed objects along the road, such as buildings, traffic barriers, and poles); (6) dynamic objects (e.g., real-time or frequently updated data about moving objects, such as other vehicles, pedestrians, and cyclists); and / or (7) positioning and location determination: precise reference points and landmarks that help to accurately locate vehicles on the map. In some specific implementations, HD maps may also include real-time information such as traffic, obstacles, construction, road closures, and / or weather conditions for different areas / roads. Because HD maps can provide detailed and up-to-date information about road networks, including lane-level data, traffic signs, road markings, and other important features, they are likely to be an important aspect enabling autonomous vehicles to navigate in complex environments and make informed decisions in real time.

[0110] Such as combination Figure 7and Figure 8 As described, while precise positioning techniques using GNSS and IMU coupling can provide highly accurate location solutions, IMU bias drift can reduce positioning accuracy during GNSS outages. This IMU bias can also cause heading ambiguity during initial sensor alignment and / or static startup. Therefore, camera vision (by positioning devices such as UEs) can be used to mitigate or reduce errors in such scenarios. In some examples, maps used for positioning and / or navigation (e.g., HD maps) can be used to verify the image fidelity of vision-assisted positioning. In some examples, using external precise positioning sources (e.g., landmarks, radio frequency (RF) identifiers / identifiers (IDs), surveillance cameras, network-based precise locations, etc.) as seeds for pseudo-measurements can significantly reduce the convergence time of the positioning engine or PPE. In some scenarios, a certain amount of convergence time can also be specified for the precise positioning solution due to IMU bias calibration and feature tracking when vision-assisted positioning begins (or is triggered / activated). Therefore, if the convergence time (or reconvergence time) of vision-assisted positioning can be reduced, vision-assisted positioning can be significantly improved.

[0111] The aspects presented herein can improve (e.g., reduce) the convergence time of vision-assisted localization (such as VAPP). These aspects can provide rapid localization for vision-assisted localization by enabling images embedded with location information to be used to eliminate (common) perceptual errors in localization devices (e.g., during GNSS outages). In one aspect of this disclosure, the convergence time of vision-based localization can be reduced based on the use of common visual features (e.g., collaborative VAPP using common visual features), where the localization device (e.g., UE, camera, vehicle, localization engine, etc.) can select a set of common environmental features in the vicinity for rapid localization (e.g., for determining location and / or attitude). In some specific implementations, the localization device may also use created and customized artificial features when such common features are not detected / unavailable. In another aspect of this disclosure, convergence time for vision-based positioning can be reduced by using map data assistance (e.g., HD map assistance), wherein the positioning device can perform feature matching with the map (e.g., HD map) to obtain an external precise location source, perform UE temporal (dynamic) model enhancement using the map, and / or perform RF-based (GNSS) positioning error modeling based on the map, etc.

[0112] In one aspect of this disclosure, a reference system can be used to assist a UE in visually assisted localization, which may be referred to as "cooperative localization" or "cooperative visually assisted localization" for the purposes of this disclosure. The reference system may include a GNSS chipset, at least one IMU, and at least one camera (e.g., a GNSS+IMU+camera system), wherein the 6DOF (e.g., localization and attitude) of the reference system may have converged. The UE (e.g., a mobile device or vehicle, also including a GNSS+IMU+camera system) can then be configured to detect / view a set of common environmental features being tracked by the reference system. The location of this set of common environmental features can be configured to be a function of the camera's 6DOF (e.g., based on the camera's 3D localization and 3D altitude). Furthermore, the relative orientations among these common environmental features may be different relative to the UE or the reference system.

[0113] The reference system can share (broadcast) the following information to the UE: the reference system's 6DOF (e.g., 3D positioning and 3D attitude), real-time GNSS measurements (e.g., in Observation State Representation (OSR) format), and / or real-time tracking features and the location of each feature. Based on the information from the reference system (which may be referred to as "reference system data"), the UE's 6DOF estimation process can be rapidly initialized and converged using the reference system data. For example, since the absolute locations of commonly visible features may be known, the UE's positioning uncertainty can be significantly reduced based on information from the UE's camera and information from the reference system regarding feature locations. Additionally, PPP / RTK can also be fixed / converged more quickly based on GNSS measurements from the reference system (e.g., the search space for integer ambiguity resolution (IAR) is much smaller). IAR can refer to the process in GNSS / GPS positioning, such as in applications like RTK and PPP, where a GNSS / GPS receiver uses signals from multiple satellites to accurately determine the user's location. The process of determining the user's location typically involves two types of ambiguity: carrier phase ambiguity and code phase ambiguity, where the IAR process may involve finding the correct integer value for the carrier phase ambiguity.

[0114] Figure 9 This is a communication flow 900 illustrating examples of collaborative visual-assisted localization based on shared environmental features according to various aspects of this disclosure. The numbers associated with the communication flow 900 do not specify a particular time order and are used only as a reference to the communication flow 900.

[0115] As shown at 950, UE 902 (e.g., mobile device, positioning device, navigation device, vehicle, etc.) may include a satellite signal receiver / chipset (e.g., a GNSS / GPS receiver / chipset) (which enables UE 902 to receive satellite signals (e.g., based on, in combination with...) Figure 5 and Figure 6 The reference system 904 (which may be another UE, another mobile device, a base station, a server, a roadside unit (RSU), a network node / entity, etc.) may also include a satellite signal receiver / chipset (which enables the reference system 904 to determine its location based on received satellite signals), at least one IMU, and at least one camera (e.g., the reference system 904 may also include a GNSS+IMU+camera system). The six degrees of freedom (6DOF) of the reference system 904 may have converged.

[0116] At 920, UE 902 may receive a list of visual features and their corresponding locations from reference system 904 (or via a server). For example, reference system 904 or the server may broadcast the list of visual features and their corresponding locations to one or more UEs within a specified area, and UEs within the specified area may receive the list of visual features and their corresponding locations broadcast by reference system 904 or the server. Visual features may refer to visual characteristics associated with an object. For example, visual features may be a specified object / building, a color pattern of an object / building, the outline of an object / building, a portion / part of an object / building, and / or the environment, such as road / street signs, text in road / street signs, tall buildings, landmarks, etc. In some implementations, visual features may be configured to be a function of the 6DOF of reference system 904 (or a camera of reference system 904). For example, visual features (e.g., a specified portion of a building) may be selected based on the 6DOF of the camera of reference system 904. In some examples, visual features may be invisible to the human eye but may be visible to machine vision (e.g., infrared, ultraviolet, X-rays, and gamma rays, etc.).

[0117] At 922, based on a list of visual features and their corresponding locations received from reference system 904 (or via a server), UE 902 may be configured to identify at least one visual feature 906 (or a combination of visual features) in a region via its camera, wherein at least one visual feature 906 (or a combination of visual features) is included in the list of visual features. This region and / or at least one visual feature 906 may be specified as being within a threshold distance of UE 902. For example, UE 902 may be configured to search for visual features within one kilometer or 300 feet of UE 902.

[0118] At 924, based on at least one visual feature 906 and the location corresponding to at least one visual feature 906, UE 902 may estimate its localization (e.g., absolute localization, relative localization, etc.) or use such information to assist the convergence of its localization engine (e.g., by narrowing the search space used for its RTK / PPP module and / or IAR process). In other words, UE 902 may perform visual-assisted localization or VAPP based on at least one visual feature 906. For example, instead of performing an IAR process over a search space with a diameter of 10 kilometers (KM), UE 902 may use the location of at least one visual feature 906 to narrow the search space to a diameter of only 1 kilometer. In another example, if the exact / absolute location of at least one visual feature 906 is known, UE 902 may also be able to determine its exact / absolute location and / or its relative location based on at least one visual feature 906. In some examples, UE 902 may also use at least one visual feature 906 to determine its past localization and / or estimate / predict its future localization. For example, if at least one visual feature 906 corresponds to a landmark and the UE 902 is moving toward that landmark, the UE 902 can predict or calculate its future and / or past location relative to that landmark.

[0119] At 926, depending on the specific implementation, UE 902 may output its estimated location or store the estimated location in memory (e.g., to another entity or application). For example, if UE 902 is a positioning engine or positioning device, UE 902 may send the estimated location to a positioning server (e.g., a location management function (LMF)) or a navigation application, etc.

[0120] In some examples, reference system 904 may send a list of visual features and their locations based on a request from UE 902. For example, as shown at 928, UE 902 may send a request to reference system 904 for a list of visual features and their corresponding locations. In response, reference system 904 may send the list of visual features and their corresponding locations to UE 902 based on this request, as shown at 920.

[0121] In another example, as shown at 930, reference system 904 may also estimate its 6DOF and / or provide its 6DOF information and / or satellite measurements (e.g., GNSS / GPS measurements) to UE 902 to further assist UE 902 in positioning. For example, UE 902 may use GNSS / GPS measurements from reference system 904 to improve / reduce its convergence time (or the convergence time of its positioning engine). For example, UE 902 may initiate a 6DOF estimation process for its positioning engine based on the location corresponding to at least one visual feature 906, the 6DOF of reference system 904, and real-time GNSS measurements from reference system 904. UE 902 may then be able to calculate its positioning (with some accuracy) after the positioning engine has converged.

[0122] Reference system 904 may transmit a list of visual features and their locations (e.g., as shown at 920) and 6DOF information and / or satellite measurements of the reference system (e.g., as shown at 930) via the same message or via separate / different messages. Additionally, reference system 904 may also transmit messages via unicast messages (e.g., messages dedicated to UE 902) or via broadcast messages (e.g., messages for multiple UEs, UEs within a region, UEs meeting certain conditions, etc.).

[0123] Combination Figure 9 The described aspects enable a reference system (e.g., reference system 904) to provide the UE (e.g., UE 902) with its 6DOF (e.g., 3D positioning and 3D attitude), GNSS measurements (e.g., in OSR format), and a list of tracked features and their locations. When the UE identifies a common feature being tracked (e.g., a stop sign, a landmark, etc.), the UE can calculate its own positioning or distance (e.g., a positioning circle) around that common feature (e.g., around a step sign, around a landmark, etc.). The UE's RTK and / or PPP IAR modules can then be triggered with a much smaller search space, allowing the IAR to be fixed and precise UE positioning to be obtained with a much shorter convergence time.

[0124] In another aspect of this disclosure, collaborative visual-assisted localization (e.g., visual-assisted localization performed by two or more entities) can also be configured to use artificial / virtual features or artificial / virtual environmental features. For the purposes of this disclosure, artificial / virtual features or artificial / virtual environmental features may refer to features or things intentionally created for collaborative visual-assisted localization (e.g., for a UE to perform visual-assisted localization based on such features). In some examples, artificial / virtual features may be visible to a camera or machine vision, but may be invisible to the human eye.

[0125] Figure 10Figure 1000 illustrates examples of collaborative visual-assisted localization based on artificial / virtual features according to various aspects of this disclosure. As shown at 1002, a reference system (e.g., reference system 904) may be configured to use a projector to (actively) create and customize a set of artificial features 1004, such as using laser projection on a 2D surface (e.g., using 2D projection on a road surface or building surface, etc.) or using laser projection in 3D space (e.g., using 3D projection at a road intersection, etc.). The projector may be part of the reference system (e.g., assigned to the reference system) or separate from the reference system (e.g., multiple projectors may be assigned to different areas and controlled by the reference system). In some examples, if the reference system is another vehicle / UE, the headlights of the vehicle or the lights of the UE may be used to create the set of artificial features 1004. Then, as in combination Figure 9 As described in 920, when the reference system 904 sends a list of visual features and their locations to the UE 902, the list of visual features may also include a set of artificial / virtual features and their locations. For example, the reference system 904 may create (or cause to generate) visual features at a specified location, and the UE 902 may attempt to capture / detect the created visual features and use such visual features to determine its location or converge its localization engine, such as by combining... Figure 9 As described in 924.

[0126] In some implementations, the reference system may also be configured to intentionally create artificial features within the UE's field of view (e.g., rather than pre-configured at fixed locations). For example, if the reference system is able to know the approximate / coarse location of the UE and / or the UE's orientation / heading (e.g., provided by the UE or obtained via another entity), the reference system may create artificial features in the UE's heading direction and / or around the UE (so that at least one camera of the UE can capture the artificial features). For example, if the reference system determines that the UE is currently near an intersection, the reference system may create a set of artificial features in and around the intersection.

[0127] In another aspect of this disclosure, in addition to or as an alternative to the reference system creating artificial / virtual features, the UE may also be configured to create artificial / virtual features, such as using its headlights to illuminate a unique identifier or pattern. In response, the reference system may attempt to detect and track the artificial / virtual features created by the UE (e.g., using one or more cameras that may or may not be assigned to the reference system). If the reference system is able to detect and track the artificial / virtual features created by the UE, it may be able to identify the UE's location and notify the UE of its location. For example, the reference system may have cameras at a designated intersection. When a UE creating a unique artificial / virtual feature passes through the intersection and is detected by the reference system's cameras, the reference system may identify that the UE is currently around the intersection and notify the UE of its location (and the UE may use this information to determine its location and / or reduce the convergence time of its positioning engine).

[0128] When there are no common (e.g., non-human) features that can be used as a reference by the reference system and the UE, such as when the UE is in a tunnel, in a garage, or in a rural nighttime environment where the environment may not provide many traceable visual features, combining Figure 10 The described artificial / virtual features may be useful.

[0129] In another aspect of this disclosure, the UE (e.g., UE 902) may also use information from a map or map data to perform or assist in vision-based positioning, such as determining its location and / or reducing the convergence time of its positioning engine by matching features in the map or map data with images captured by the UE (or by the UE's camera). For example, as described above, a high-definition (HD) map may be a highly detailed and accurate digital map that includes real-time information, some of which may be used by the UE to determine its location (e.g., absolute or relative location, etc.).

[0130] Figure 11Figure 1100 illustrates examples of visually assisted localization based on feature matching with a map, according to various aspects of this disclosure. In one example, map data (or a set of maps) (such as HD map data or HD maps) may include both invariant and variable components. An invariant component (which may also be referred to as an invariant feature) may refer to objects that are likely to remain unchanged (e.g., remain constant) over a relatively long period of time (e.g., in the real world). For example, as shown at 1110, building 1112, fire hydrant 1114, and / or road sign 1116 may be considered invariant components because they are more likely to remain unchanged over a relatively long period of time (e.g., typically lasting at least several months or years). On the other hand, a variable component (which may also be referred to as a variable feature) may refer to objects that are more likely to change over a relatively short period of time (e.g., typically within months, days, etc.). For example, flag 1118 and pedestrian crossing 1120 may be considered variable components because they may change over a shorter period of time compared to constant components (e.g., the shape of flag 1118 may change depending on the wind direction, and the color and outline of pedestrian crossing 1120 may fade or wear over time, etc.).

[0131] In one example, UE 1102 may use information provided by map data to achieve fast localization (or faster convergence time) for vision-based positioning, such as by matching invariant features or FOV in the map data with features or FOV from images / views captured by UE 1102 (via at least one camera of UE 1102). In some examples, the map used by UE 1102 may be stored in a local database or local map database of UE 1102. A local database or local map database may refer to at least one memory located within UE 1102 and directly accessible by UE 1102 (e.g., typically without traversing another entity). In some examples, UE 1102 may be configured to periodically or based on certain conditions (e.g., when entering an area without a map) download map data (or updated map data) from server 1104 (e.g., a map server / database) to keep its local map database up-to-date (e.g., for navigation and / or autonomous driving purposes, etc.). A local map database can refer to map data stored in the UE's memory that can be accessed by the UE without being downloaded from another source such as a server.

[0132] In one aspect, UE 1102 may use an object location seeding mechanism to perform visually assisted localization based on feature matching with a map, wherein UE 1102 may obtain the location of matching features directly from map data or server 1104. For the purposes of this disclosure, a matching feature may refer to a feature (e.g., an object, building, pattern, etc.) detected in an image / FOV captured by the UE that matches the same feature in the map / map data. For example, as shown at 1110, UE 1102 may be able to identify features such as building 1112, fire hydrant 1114, and / or road sign 1116 from an image / FOV captured by UE 1102, and UE 1102 may match them with the same building, fire hydrant, and / or road sign in the map data. Thus, these features may be referred to as matching features.

[0133] Based on these matching features, UE 1102 may be able to determine / obtain the exact / approximate location of these features from map data (e.g., map data may include the location of objects) or from server 1104 (e.g., UE 1102 may request server 1104 to provide the location of these matching features). For example, as shown at 1110, after UE 1102 identifies building 1112, fire hydrant 1114, and / or road sign 1116 from an image / FOV captured by UE 1102 and matches them with the same building, fire hydrant, and / or road sign in map data, UE 1102 may be able to know the exact / approximate location of building 1112, fire hydrant 1114, and / or road sign 1116 (e.g., map data may include location information of these features, such as their addresses or coordinates). Then, based on knowing their locations, UE 1102 can determine its absolute / approximate location (e.g., relative location techniques can be used to solve for the UE's location) and / or its relative location to at least one of these features (e.g., 2 km southeast of building 1112), and UE 1102 can also use the determined location / relative location to enhance / reduce the convergence time of its positioning engine, such as by combining... Figure 9 The description (e.g., similar to using at least one visual feature 906 with its corresponding position to achieve fast localization / faster convergence of the localization engine).

[0134] On the other hand, UE 1102 can perform visually assisted localization using an FOV location seeding mechanism based on feature matching with a map. UE 1102 can calculate and determine its 6DOF by matching its FOV (e.g., a view / image captured by UE 1102 via at least one camera) with the FOV from map data. For example, if UE 1102 is able to match its FOV (as shown at 1110) with the same FOV from map data, then UE 1102 (or server 1104) can be able to calculate and estimate UE 1102's 6DOF. In other words, based on the FOV of a map (e.g., an HD map including street views), the viewer's (e.g., UE's) 6DOF can be determined from the HD map using feature / FOV matching (e.g., this can also be done in server 1104 or via a cloud server, etc.). Then, based on knowing UE 1102's 6DOF, UE 1102 can be able to determine its location (e.g., absolute location, approximate location, or relative location). For example, in order for a camera to capture the view shown at location 1110 based on a set of camera settings (e.g., having a specified focal length, zoom, and / or resolution, etc.), the camera may be located in a specified area (e.g., between 5 and 6 meters from the intersection and facing north). Similarly, after determining its location, UE 1102 can use the determined location to enhance / reduce the convergence time of its positioning engine and / or achieve fast positioning of its positioning engine, such as by combining... Figure 9 The description (e.g., similar to using at least one visual feature 906 and its corresponding location to achieve fast localization / faster convergence of the localization engine).

[0135] Figure 12 Figure 1200 illustrates examples of UE time (dynamic) model enhancements using maps (e.g., HD maps) according to various aspects of this disclosure. In another aspect of this disclosure, since maps (e.g., HD maps) can provide extensive information including real-time information as described above, in some embodiments, the map may also include the trajectory of ground vehicles, for example, the location of ground vehicles changing over time. For example, as shown at 1210, map 1202 (e.g., HD map) may include the trajectories of UE 1204 (e.g., vehicles), such as their locations at a first time point (T1), a second time point (T2), a third time point (T3), and up to the Nth time point (TN).

[0136] In one aspect, since the map (or map data) can also provide the relationship between the height and latitude / longitude of the UE (e.g., UE 902), this information can be used as a complete constraint for (estimating) the UE's dynamics. For the purposes of this disclosure, a system can be classified / defined as complete if (all) its constraints are complete. To make a constraint complete, it can be specified as being expressible as a function (e.g., a complete constraint may depend only on coordinates and possibly on time). For example, when lane-level positioning is available (e.g., positioning with sufficient accuracy that allows the UE to determine the lane it is traveling in), the trajectory information from map 1202 shown at 1210 can also be configured to feed into the positioning engine (of visual-assisted positioning or VAPP) so that the positioning engine (of the UE) can obtain a more accurate temporal (dynamic) model of the UE. The obtained temporal (dynamic) model can then be used in a Kalman filtering (KF) process for state prediction based on a physical model, such as Figure 13 As shown in Figure 1300. A better time (dynamic) model may be beneficial in enabling the UE to produce more accurate and faster positioning (e.g., faster convergence time) in challenging environments, such as in deep urban areas for GNSS / GPS positioning, and / or during nighttime for vision-based positioning.

[0137] In another aspect of this disclosure, the UE (e.g., UE 902) may also be configured to perform RF-based positioning error modeling using information from a map (e.g., an HD map), wherein radio frequency (RF)-based positioning may refer to positioning involving receiving and / or transmitting RF (e.g., wireless) signals. For example, in combination with Figure 4 The described network-based localization and combination Figure 5 and Figure 6 The GNSS-based positioning described can be referred to as RF-based positioning.

[0138] In some specific implementations, since the map (e.g., an HD map) may also contain environmental information (e.g., weather conditions, temperature, pollution levels, etc.) and the (rough) location of the UE (e.g., UE 902) can be estimated from the map (e.g., based on the estimated location / trajectory of UE 902 in the map, such as in combination with...) Figure 12As described, the (coarse) location of the UE can therefore be configured to be associated with satellite (e.g., GNSS / GPS) measurement errors (e.g., in Observation State Representation (OSR) format or State Space Representation (SSR) format, etc.). Thus, the map (or map data) can also be configured to include (such as crowdsourcing or experience-based modeling) a budget of satellite (GNSS / GPS) measurement errors received from multiple sources (e.g., provided by multiple users). For example, a group of UEs / vehicles can be configured to provide their GNSS / GPS measurements and errors to a cloud server. The GNSS / GPS error budget can then be modeled in a specified format (e.g., SSR format) based on the location input (of the UE providing the measurements). For example, error modeling using a map can be associated with multipath effects, where a 3D building model from the map can be used to model multipath using RF signal ray tracing. In another example, error modeling using a map can be associated with vibrations of the Earth's surface, because ground vibrations (e.g., those of bridges, railways, etc.) can be highly dependent on the environment, where for high-precision positioning, a shift of several centimeters from a particular location might occur. In another example, error modeling using maps can be correlated with satellite (GNSS / GPS) signal interference (e.g., based on interference and spoofing heatmaps). In yet another example, error modeling using maps can be correlated with atmospheric effects (e.g., ionospheric effects / impacts on satellite signals) where atmospheric effects can be obtained from maps (e.g., HD maps) by integrating with real-time spatial and meteorological sources. In some examples, the total satellite (GNSS / GPS) error budget can also be modeled in OSR format based on historical UE data.

[0139] The aspects presented in this paper relate to enhancements related to Visual Assisted Precision Positioning (VAPP). The aspects presented in this paper include the following aspects / features: (1) Collaborative VAPP using common visual features—(a) selecting common environmental features in the vicinity for rapid positioning (elevation and location), and (b) creating and customizing artificial features when common features are not detected; (2) HD map-assisted VAPP—(a) feature matching with HD maps to obtain external precise location sources, and (b) using HD maps for UE temporal (dynamic) model enhancement, and (c) RF-based (GNSS) positioning error modeling based on HD maps.

[0140] Figure 14This is a flowchart 1400 of a wireless communication method. The method can be performed by a UE (e.g., UE 104, 404, 902, 1102; GNSS device 506; rover device 604; vehicle 702; device 1604). The method can improve (e.g., reduce) the convergence time of visual-assisted positioning by enabling the UE to use images embedded with location information.

[0141] At 1404, the UE can receive a list of visual features and the location of each visual feature in the list from a reference device, server, or map, such as combining... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 920, UE902 may receive a list of visual features and their corresponding locations from reference system 904 (or via a server). Receiving this list of visual features may be achieved by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0142] At 1408, the UE can identify at least one visual feature in a region via at least one camera, wherein the at least one visual feature is included in the list of visual features, and wherein the region is within a threshold distance of the UE, such as in combination Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 922, based on a list of visual features received from reference system 904 (or via a server) and their corresponding locations, UE 902 can be configured to identify at least one visual feature 906 (or a combination of visual features) in a region via its camera, wherein at least one visual feature 906 (or a combination of visual features) is included in the list of visual features. Identification of the at least one visual feature can be achieved by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0143] At 1410, the UE can estimate its location based on at least one identified visual feature in the area and the location corresponding to that at least one visual feature, such as by combining... Figures 9 to 12 As described. For example, as in combination Figure 9As discussed in section 924, based on at least one visual feature 906 and the location corresponding to at least one visual feature 906, UE 902 may estimate its localization or use such information to assist the convergence of its localization engine (e.g., by narrowing the search space used for its RTK / PPP module and / or IAR process). Receiving this list of visual features may be achieved by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0144] In one example, the UE may send a request for the visual feature list to the reference device before receiving the list, such as combining... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 928, UE 902 may send a request to reference system 904 for a list of visual features and their corresponding locations. In response, reference system 904 may send the list of visual features and their corresponding locations to UE 902 based on the request, as shown in section 920. This request may be sent by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0145] In another example, the UE can receive 6DOF and real-time GNSS measurements from the reference device, such as combined with... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 930, UE 902 may receive 6DOF information and / or satellite measurements (e.g., GNSS / GPS measurements) from reference system 904 to further assist UE 902 in positioning. Receiving the 6DOF and real-time GNSS measurements from this reference system may be achieved by, for example... Figure 16The device 1604 comprises a visual-assisted positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606. In some embodiments, the reference device may include a GNSS module, at least one IMU, and one or more cameras, wherein the 6DOF of the reference device is converged. In some embodiments, to estimate the UE's location based on at least one identified visual feature in the area and the location corresponding to the at least one visual feature, the UE may initiate a 6DOF estimation process for a positioning engine based on the location corresponding to the at least one visual feature, the 6DOF of the reference device, and the real-time GNSS measurement, and the UE may calculate the UE's location after the positioning engine converges. In some specific implementations, in order to receive the list of visual features, the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement, the UE may receive the list of visual features, the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement via broadcast or unicast messages.

[0146] In another example, the UE can output an indication of the estimated location of the UE, such as in conjunction with... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 926, depending on the specific implementation, UE 902 may (e.g., to another entity or application) output its estimated location or store the estimated location in memory. Outputting this indication may be done by, for example... Figure 16 The device 1604 includes a visual-assisted positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606. In some embodiments, in order to output the indication of the estimated location of the UE, the UE may send the indication of the estimated location of the UE or store the indication of the estimated location of the UE.

[0147] In another example, the location of the UE can be at least one of the following: the relative location of the UE, the past location of the UE, the current location of the UE, or the estimated future location of the UE.

[0148] In another example, each visual feature in the list of visual features may correspond to an object in the environment, a part of that object, or a property of that object.

[0149] In another example, in order to estimate the location of the UE, the UE may estimate the location of the UE based on VAPP.

[0150] In another example, the location corresponding to the at least one visual feature can be a function of the 6DOF of the at least one camera.

[0151] In another example, the list of visual features may include a set of artificial features, and the at least one visual feature may include at least one artificial feature from the set of artificial features. In some specific implementations, the set of artificial features may correspond to a set of light projections.

[0152] In another example, the server may be a local map database, a map server, or an environment server, and the list of visual features may be based on visual features presented in the map from the local map database, the map server, or the environment server.

[0153] In another example, the UE may obtain a set of vehicle trajectory information (e.g., from the local map database, the map server, or the environment server), and in order to estimate the UE's location, the UE may further estimate the UE's location based on the trajectory information.

[0154] In another example, the UE may obtain information associated with the GNSS measurement error budget (e.g., from the local map database, the map server, or the environment server), and in order to estimate the UE's location, the UE may further estimate the UE's location based on the information associated with the GNSS measurement error budget.

[0155] Figure 15 This is a flowchart 1500 of a wireless communication method. The method can be performed by a UE (e.g., UE 104, 404, 902, 1102; GNSS device 506; rover device 604; vehicle 702; device 1604). The method can improve (e.g., reduce) the convergence time of visual-assisted positioning by enabling the UE to use images embedded with location information.

[0156] At 1504, the UE can receive a list of visual features and the location of each visual feature in the list from a reference device, server, or map, such as combining... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 920, UE902 may receive a list of visual features and their corresponding locations from reference system 904 (or via a server). Receiving this list of visual features may be achieved by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0157] At 1508, the UE can identify at least one visual feature in a region via at least one camera, wherein the at least one visual feature is included in the list of visual features, and wherein the region is within a threshold distance of the UE, such as in combination with Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 922, based on a list of visual features received from reference system 904 (or via a server) and their corresponding locations, UE 902 can be configured to identify at least one visual feature 906 (or a combination of visual features) in a region via its camera, wherein at least one visual feature 906 (or a combination of visual features) is included in the list of visual features. Identification of the at least one visual feature can be achieved by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0158] At 1510, the UE can estimate its location based on at least one identified visual feature in the area and the location corresponding to that at least one visual feature, such as by combining... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 924, based on at least one visual feature 906 and the location corresponding to at least one visual feature 906, UE 902 may estimate its localization or use such information to assist the convergence of its localization engine (e.g., by narrowing the search space used for its RTK / PPP module and / or IAR process). Receiving this list of visual features may be achieved by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0159] In one example, as shown at 1502, the UE may send a request for the visual feature list to the reference device before receiving the list, such as combining... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 928, UE 902 may send a request to reference system 904 for a list of visual features and their corresponding locations. In response, reference system 904 may send the list of visual features and their corresponding locations to UE 902 based on the request, as shown in section 920. This request may be sent by, for example... Figure 16 The device 1604 is executed by a visual aid positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606.

[0160] In another example, as shown at 1506, the UE can receive 6DOF and real-time GNSS measurements from the reference device, such as combined with... Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 930, UE 902 may receive 6DOF information and / or satellite measurements (e.g., GNSS / GPS measurements) from reference system 904 to further assist UE 902 in positioning. Receiving the 6DOF and real-time GNSS measurements from this reference system may be achieved by, for example... Figure 16 The device 1604 comprises a visual-assisted positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606. In some embodiments, the reference device may include a GNSS module, at least one IMU, and one or more cameras, wherein the 6DOF of the reference device is converged. In some embodiments, to estimate the UE's location based on at least one identified visual feature in the area and the location corresponding to the at least one visual feature, the UE may initiate a 6DOF estimation process for a positioning engine based on the location corresponding to the at least one visual feature, the 6DOF of the reference device, and the real-time GNSS measurement, and the UE may calculate the UE's location after the positioning engine converges. In some specific implementations, in order to receive the list of visual features, the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement, the UE may receive the list of visual features, the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement via broadcast or unicast messages.

[0161] In another example, as shown at 1512, the UE can output an indication of the estimated location of the UE, such as in conjunction with Figures 9 to 12 As described. For example, as in combination Figure 9 As discussed in section 926, depending on the specific implementation, UE 902 may (e.g., to another entity or application) output its estimated location or store the estimated location in memory. Outputting this indication may be done by, for example... Figure 16 The device 1604 includes a visual-assisted positioning component 198, a camera 1632, one or more sensors 1618, a transceiver 1622, a cellular baseband processor 1624, and / or an application processor 1606. In some embodiments, in order to output the indication of the estimated location of the UE, the UE may send the indication of the estimated location of the UE or store the indication of the estimated location of the UE.

[0162] In another example, the location of the UE can be at least one of the following: the relative location of the UE, the past location of the UE, the current location of the UE, or the estimated future location of the UE.

[0163] In another example, each visual feature in the list of visual features may correspond to an object in the environment, a part of that object, or a property of that object.

[0164] In another example, in order to estimate the location of the UE, the UE may estimate the location of the UE based on VAPP.

[0165] In another example, the location corresponding to the at least one visual feature can be a function of the 6DOF of the at least one camera.

[0166] In another example, the list of visual features may include a set of artificial features, and the at least one visual feature may include at least one artificial feature from the set of artificial features. In some specific implementations, the set of artificial features may correspond to a set of light projections.

[0167] In another example, the server may be a local map database, a map server, or an environment server, and the list of visual features may be based on visual features presented in a map from the local map database, the map server, or the environment server.

[0168] In another example, the UE can obtain trajectory information of a set of vehicles, and in order to estimate the UE's location, the UE can further estimate the UE's location based on the trajectory information.

[0169] In another example, the UE may obtain information associated with the GNSS measurement error budget, and in order to estimate the UE's position, the UE may further estimate the UE's position based on the information associated with the GNSS measurement error budget.

[0170] Figure 16Figure 1600 illustrates an example of a hardware implementation for device 1604. Device 1604 may be a UE, a component of a UE, or implement UE functionality. In some aspects, device 1604 may include at least one cellular baseband processor 1624 (also referred to as a modem) coupled to one or more transceivers 1622 (e.g., cellular RF transceivers). Cellular baseband processor 1624 may include at least one on-chip memory 1624'. In some aspects, device 1604 may also include one or more Subscriber Identity Module (SIM) cards 1620 and at least one application processor 1606 coupled to a Secure Digital Card (SD) card 1608 and a screen 1610. Application processor 1606 may include on-chip memory 1606'. In some aspects, device 1604 may also include a Bluetooth module 1612, a WLAN module 1614, an ultra-wideband (UWB) module 1638, an in-cabin monitoring system (ICMS) 1640, an SPS module 1616 (e.g., a GNSS module), one or more sensors 1618 (e.g., barometers / altimeters); motion sensors such as inertial measurement units (IMUs), gyroscopes and / or accelerometers; light detection and ranging (LIDAR), radio-assisted detection and ranging (RADAR), sound navigation and ranging (SONAR), magnetometers, audio and / or other technologies for positioning), an additional memory module 1626, a power source 1630, and / or a camera 1632. Bluetooth module 1612, UWB module 1638, ICMS module 1640, WLAN module 1614, and SPS module 1616 may include on-chip transceivers (TRXs) (or in some cases, only receivers (RXs)). Bluetooth module 1612, WLAN module 1614, and SPS module 1616 may include their own dedicated antennas and / or communicate using antenna 1680. Cellular baseband processor 1624 communicates with UE 104 and / or with RUs associated with network entity 1602 via transceiver 1622 through one or more antennas 1680. Cellular baseband processor 1624 and application processor 1606 may each include computer-readable media / memory 1624', 1606'. Additional memory module 1626 may also be considered as computer-readable media / memory. Each computer-readable medium / memory 1624', 1606', 1626 may be non-transitory. Cellular baseband processor 1624 and application processor 1606 are each responsible for general processing, including executing software stored on the computer-readable medium / memory. When executed by cellular baseband processor 1624 / application processor 1606, the software causes cellular baseband processor 1624 / application processor 1606 to perform the various functions described above. The cellular baseband processor 1624 and application processor 1606 are configured to perform the various functions described above, at least in part, based on information stored in memory.In other words, the cellular baseband processor 1624 and application processor 1606 can be configured to perform a first subset of the various functions described above without information stored in memory, and can be configured to perform a second subset of the various functions described above based on information stored in memory. The computer-readable medium / memory can also be used to store data manipulated by the cellular baseband processor 1624 / application processor 1606 during software execution. The cellular baseband processor 1624 / application processor 1606 can be a component of the UE 350 and can include at least one of a memory 360 and / or at least one of a TX processor 368, an RX processor 356, and a controller / processor 359. In one configuration, the device 1604 can be at least one processor chip (modem and / or application) and includes only the cellular baseband processor 1624 and / or application processor 1606, while in another configuration, the device 1604 can be the entire UE (e.g., see [link]). Figure 3 The UE 350 includes an additional module of the device 1604.

[0171] As discussed above, the visual-assisted positioning component 198 can be configured to receive a list of visual features and the location of each visual feature in the list from a reference device, server, or map. The visual-assisted positioning component 198 can also be configured to identify at least one visual feature in an area via at least one camera, wherein the at least one visual feature is included in the list of visual features, and wherein the area is within a threshold distance of the UE. The visual-assisted positioning component 198 can also be configured to estimate the UE's location based on the identified at least one visual feature in the area and the location corresponding to the at least one visual feature. The visual-assisted positioning component 198 may be located within the cellular baseband processor 1624, the application processor 1606, or both the cellular baseband processor 1624 and the application processor 1606. The visual-assisted positioning component 198 may be one or more hardware components specifically configured to execute the process / algorithm, implemented by one or more processors configured to execute the process / algorithm, stored in a computer-readable medium for implementation by one or more processors, or some combination thereof. When multiple processors are implemented, the multiple processors may execute the stated process / algorithm individually or in combination. As shown in the figure, device 1604 may include various components configured for various functions. In one configuration, device 1604 (and specifically, cellular baseband processor 1624 and / or application processor 1606) may include components for receiving a list of visual features and the location of each visual feature in the list from a reference device, server, or map. Device 1604 may also include components for identifying at least one visual feature in an area via at least one camera, wherein the at least one visual feature is included in the list of visual features, and wherein the area is within a threshold distance of the UE. Device 1604 may also include components for estimating the location of the UE based on the identified at least one visual feature in the area and the location corresponding to the at least one visual feature.

[0172] In one configuration, the device 1604 may further include components for sending a request for the visual feature list to the reference device before receiving the list.

[0173] In another configuration, device 1604 may further include components for receiving 6DOF and real-time GNSS measurements from the reference device. In some embodiments, the reference device may include a GNSS module, at least one IMU, and one or more cameras, wherein the 6DOF of the reference device is converged. In some embodiments, the components for estimating the UE's location based on at least one identified visual feature in the area and the location corresponding to the at least one visual feature may include configuring device 1604 to initiate a 6DOF estimation process for a positioning engine based on the location corresponding to the at least one visual feature, the 6DOF of the reference device, and the real-time GNSS measurements, and to calculate the UE's location after the positioning engine converges. In some specific implementations, the component for receiving the list of visual features, the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement may include configuring the device 1604 to receive the list of visual features, the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement via broadcast or unicast messages.

[0174] In another configuration, device 1604 may further include components for outputting an indication of the estimated location of the UE. In some specific embodiments, the components for outputting the indication of the estimated location of the UE may include configuring device 1604 to either send the indication of the estimated location of the UE or store the indication of the estimated location of the UE.

[0175] In another configuration, the location of the UE can be at least one of the following: the relative location of the UE, the past location of the UE, the current location of the UE, or the estimated future location of the UE.

[0176] In another configuration, each visual feature in the list of visual features may correspond to an object in the environment, a part of that object, or a property of that object.

[0177] In another configuration, the component for estimating the location of the UE may include configuring the device 1604 to estimate the location of the UE based on VAPP.

[0178] In another configuration, the position corresponding to the at least one visual feature can be a function of the 6DOF of the at least one camera.

[0179] In another configuration, the list of visual features may include a set of artificial features, wherein the at least one visual feature may include at least one artificial feature from the set of artificial features. In some specific implementations, the set of artificial features may correspond to a set of light projections.

[0180] In another configuration, the server may be a local map database, a map server, or an environment server, and the list of visual features may be based on visual features presented in a map from the map server or the environment server. In some embodiments, the device 1604 may further include components for obtaining trajectory information of a set of vehicles, and the components for estimating the location of the UE may include configuring the device 1604 to further estimate the location of the UE based on the trajectory information. In some embodiments, the device 1604 may further include components for obtaining information associated with a GNSS measurement error budget, and the components for estimating the location of the UE may include configuring the device 1604 to further estimate the location of the UE based on the information associated with the GNSS measurement error budget.

[0181] The component may be a vision-assisted positioning component 198 of device 1604 configured to perform the functions described therein. As described above, device 1604 may include a TX processor 368, an RX processor 356, and a controller / processor 359. Therefore, in one configuration, the component may be the TX processor 368, the RX processor 356, and / or the controller / processor 359 configured to perform the functions described therein.

[0182] Figure 17 This is a flowchart 1700 of a wireless communication method. The method can be performed by a reference device (e.g., one or more location servers 168; base stations 102, 602; reference system 904; server 1104; network entity 1960). The method enables the reference device to provide reference information to the UE to assist the UE in visual-assisted positioning.

[0183] At 1704, the reference system can estimate the 6DOF of the reference device, such as in combination. Figure 9 As described. For example, as in combination Figure 9 As discussed in 930, reference system 904 may also estimate its 6DOF and / or provide its 6DOF information and / or satellite measurements (e.g., GNSS / GPS measurements) to UE 902 to further assist UE 902 in positioning. The 6DOF estimation may be achieved by, for example... Figure 19 The reference information generation component 199, network processor 1912, and / or network interface 1980 of the network entity 1960 are executed.

[0184] At 1706, the reference system can transmit a list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and a set of GNSS measurements, such as those combined with... Figure 9 As described. For example, as in combination Figure 9As discussed in section 920, reference system 904 can send a list of visual features and their corresponding locations to UE 902. (As combined with...) Figure 9 As discussed in 930, the reference system 904 may also provide its 6DOF information and / or satellite measurements (e.g., GNSS / GPS measurements) to the UE 902 to further assist the UE 902 in positioning. The transmission of this list of visual features, the 6DOF of the reference device, and the set of GNSS measurements can be, for example, by... Figure 19 The reference information generation component 199, network processor 1912, and / or network interface 1980 of the network entity 1960 are executed.

[0185] In one example, the reference system may receive a request for the visual feature list from the UE before sending the list, such as combining... Figure 9 As described. For example, as in combination Figure 9 As discussed in section 928, reference system 904 can receive a request from UE 902 for the list of visual features and their corresponding locations. Receiving this request can be achieved by, for example... Figure 19 The reference information generation component 199, network processor 1912, and / or network interface 1980 of network entity 1960 are executed. In some specific implementations, in order to send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements, the reference system may, in response to the request, send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements to the UE.

[0186] In another example, each visual feature in the list of visual features may correspond to an object in the environment, a part of that object, or a property of that object.

[0187] In another example, the reference device may include a GNSS module, at least one IMU, and one or more cameras.

[0188] In another example, the 6DOF of the reference device may converge before sending the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements.

[0189] In another example, in order to send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements, the reference device may send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements via broadcast or unicast messages.

[0190] In another example, the list of visual features may include a set of artificial features. In some implementations, this set of artificial features may correspond to a set of optical projections. In some implementations, the reference device may project at least one visual feature from the list of visual features via a projection module, or cause at least one projection device to project the at least one visual feature.

[0191] In another configuration, the reference device may be associated with a local map database, a map server, or an environment server, and the list of visual features may be based on visual features presented in the map from the map server or the environment server.

[0192] Figure 18 This is a flowchart 1800 of a wireless communication method. The method can be performed by a reference device (e.g., one or more location servers 168; base stations 102, 602; reference system 904; server 1104; network entity 1960). The method enables the reference device to provide reference information to the UE to assist the UE in visual-assisted positioning.

[0193] At 1804, the reference system can estimate the 6DOF of the reference device, such as in combination. Figure 9 As described. For example, as in combination Figure 9 As discussed in 930, reference system 904 may also estimate its 6DOF and / or provide its 6DOF information and / or satellite measurements (e.g., GNSS / GPS measurements) to UE 902 to further assist UE 902 in positioning. The 6DOF estimation may be achieved by, for example... Figure 19 The reference information generation component 199, network processor 1912, and / or network interface 1980 of the network entity 1960 are executed.

[0194] At 1806, the reference system can transmit a list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and a set of GNSS measurements, such as those combined with... Figure 9 As described. For example, as in combination Figure 9 As discussed in section 920, reference system 904 can send a list of visual features and their corresponding locations to UE 902. (As combined with...) Figure 9 As discussed in 930, the reference system 904 may also provide its 6DOF information and / or satellite measurements (e.g., GNSS / GPS measurements) to the UE 902 to further assist the UE 902 in positioning. The transmission of this list of visual features, the 6DOF of the reference device, and the set of GNSS measurements can be, for example, by... Figure 19 The reference information generation component 199, network processor 1912, and / or network interface 1980 of the network entity 1960 are executed.

[0195] In one example, as shown at 1802, the reference system may receive a request for the visual feature list from the UE before sending the list, such as combining... Figure 9 As described. For example, as in combination Figure 9 As discussed in section 928, reference system 904 can receive a request from UE 902 for the list of visual features and their corresponding locations. Receiving this request can be achieved by, for example... Figure 19 The reference information generation component 199, network processor 1912, and / or network interface 1980 of network entity 1960 are executed. In some specific implementations, in order to send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements, the reference system may, in response to the request, send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements to the UE.

[0196] In another example, each visual feature in the list of visual features may correspond to an object in the environment, a part of that object, or a property of that object.

[0197] In another example, the reference device may include a GNSS module, at least one IMU, and one or more cameras.

[0198] In another example, the 6DOF of the reference device may converge before sending the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements.

[0199] In another example, in order to send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements, the reference device may send the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements via broadcast or unicast messages.

[0200] In another example, the list of visual features may include a set of artificial features. In some implementations, this set of artificial features may correspond to a set of optical projections. In some implementations, the reference device may project at least one visual feature from the list of visual features via a projection module, or cause at least one projection device to project the at least one visual feature.

[0201] In another configuration, the reference device may be associated with a local map database, a map server, or an environment server, and the list of visual features may be based on visual features presented in the map from the map server or the environment server.

[0202] Figure 19 Figure 1900 illustrates an example of a hardware implementation for network entity 1960. In one example, network entity 1960 may be within core network 120. Network entity 1960 may include at least one network processor 1912. Network processor 1912 may include on-chip memory 1912'. In some aspects, network entity 1960 may also include an additional memory module 1914. Network entity 1960 communicates with CU 1902 directly (e.g., via a backhaul link) or indirectly (e.g., via RIC) through network interface 1980. On-chip memory 1912' and additional memory module 1914 may each be considered as computer-readable media / memory. Each computer-readable media / memory may be non-transitory. Network processor 1912 is responsible for general processing, including executing software stored on the computer-readable media / memory. This software, when executed by a corresponding processor, causes that processor to perform the various functions described above. The computer-readable media / memory may also be used to store data manipulated by the processor while executing the software.

[0203] As discussed above, the reference information generation component 199 can be configured to send a first indication of map data to the UE. The reference information generation component 199 can also be configured to estimate the 6DOF of the reference device. The reference information generation component 199 can also be configured to send a list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and a set of GNSS measurements. The reference information generation component 199 can be within the network processor 1912. The reference information generation component 199 can be one or more hardware components specifically configured to execute the process / algorithm, implemented by one or more processors configured to execute the process / algorithm, stored in a computer-readable medium for implementation by one or more processors, or some combination thereof. When multiple processors are implemented, the multiple processors can execute the stated process / algorithm individually or in combination. The network entity 1960 can include various components configured for various functions. In one configuration, the network entity 1960 can include components for estimating the 6DOF of the reference device. Network entity 1960 may also include components for transmitting a list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and a set of GNSS measurements.

[0204] In one configuration, network entity 1960 may further include components for receiving a request for the visual feature list from the UE before transmitting the list. In some specific implementations, the components for transmitting the visual feature list and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements may include configuring network entity 1960 to transmit the visual feature list and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements to the UE in response to the request.

[0205] In another configuration, each visual feature in the list of visual features may correspond to an object in the environment, a part of that object, or a property of that object.

[0206] In another configuration, the reference device may include a GNSS module, at least one IMU, and one or more cameras.

[0207] In another configuration, the 6DOF of the reference device may converge before sending the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements.

[0208] In another configuration, the component for transmitting the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements may include configuring network entity 1960 to transmit the list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements to the UE via broadcast or unicast messages.

[0209] In another configuration, the list of visual features may include a set of artificial features. In some embodiments, the set of artificial features may correspond to a set of optical projections. In some embodiments, network entity 1960 may also include: components for projecting at least one visual feature from the list of visual features via a projection module, or components for causing at least one projection device to project the at least one visual feature.

[0210] In another configuration, network entity 1960 may be associated with a local map database, a map server, or an environment server, and the list of visual features may be based on visual features presented in the map from the map server or the environment server.

[0211] The component may be a reference information generation component 199 of network entity 1960, configured to perform the functions described by the component.

[0212] It should be understood that the specific order or hierarchy of the boxes in the disclosed process / flowcharts is merely an example of the exemplary method. It should be understood that the specific order or hierarchy of the boxes in the process / flowcharts may be rearranged based on design preferences. Furthermore, some boxes may be combined or omitted. The appended method claims present the elements of various boxes in a sample order, but are not limited to the given specific order or hierarchy.

[0213] The foregoing description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects. Therefore, the claims are not limited to the aspects described herein but should be given the full scope consistent with the language of the claims. Unless specifically stated otherwise, references to elements in the singular form do not mean “one and only one” but rather “one or more.” Terms such as “if,” “when,” and “simultaneously” do not imply a direct temporal relationship or reaction. That is, these phrases, such as “when,” do not imply an immediate action in response to the occurrence of an action or during the occurrence of an action, but simply suggest that if a condition is met, then the action will occur, without requiring a specific or immediate time limit for the occurrence of the action. The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” is not necessarily to be construed as preferred or superior to other aspects. Unless specifically stated otherwise, the term “some” refers to one or more. Combinations such as "at least one of A, B, or C", "one or more of A, B, or C", "at least one of A, B, and C", "one or more of A, B, and C", and "A, B, C, or any combination thereof" include any combination of A, B, and / or C, and may include multiple A, multiple B, or multiple C. Specifically, combinations such as "at least one of A, B, or C", "one or more of A, B, or C", "at least one of A, B, and C", "one or more of A, B, and C", and "A, B, C, or any combination thereof" can be only A, only B, only C, A and B, A and C, B and C, or A and B and C, where any such combination may contain one or more members of A, B, or C. A set should be interpreted as a collection of elements with a number of one or more elements. Therefore, for a set of X, X will include one or more elements. When at least one processor is configured to execute a set of functions, the at least one processor is configured to execute the set of functions individually or in any combination. Therefore, each of the at least one processor can be configured to perform a specific subset of the set of functions, wherein the subset is the complete set, a suitable subset of the set, or an empty subset of the set. If the first device receives data from or sends data to the second device, data can be received / sent directly between the first and second devices, or indirectly between the first and second devices via a set of devices. A device configured to “output” data (such as transmission, signaling, or a message) can, for example, transmit the data using a transceiver, or can transmit the data to the device that sent the data. A device configured to “receive” data (such as transmission, signaling, or a message) can, for example, receive the data using a transceiver, or can obtain the data from the device that received the data.Information stored in memory includes instructions and / or data. All structural and functional equivalents of the elements throughout the various aspects described herein that are known to or will later be known to a person skilled in the art are expressly incorporated herein by reference and are covered by the claims. Furthermore, nothing disclosed herein is intended to be offered to the public, whether or not such disclosure is expressly recited in the claims. The terms “module,” “mechanism,” “element,” “device,” etc., cannot replace the word “component.” Therefore, no claim element will be construed as a functional component unless the element is expressly recited using the phrase “component for…”.

[0214] As used in this article, the phrase “based on” should not be interpreted as referring to a closed set of information, one or more conditions, one or more factors, etc. In other words, the phrase “based on A” (where “A” can be information, conditions, factors, etc.) should be interpreted as “based on at least A”, unless specifically stated differently.

[0215] The following aspects are merely illustrative and may be combined with other aspects or teachings described herein without limitation.

[0216] Aspect 1 is a method for wireless communication at a user equipment (UE), the method comprising: receiving a list of visual features and the location of each visual feature in the list of visual features from a reference device, a server, or a map; identifying at least one visual feature in a region via at least one camera, wherein the at least one visual feature is included in the list of visual features, wherein the region is within a threshold distance of the UE; and estimating the location of the UE based on the identified at least one visual feature in the region and the location corresponding to the at least one visual feature.

[0217] Aspect 2 is the method according to aspect 1, the method further comprising: outputting an indication of the estimated location of the UE.

[0218] Aspect 3 is the method according to aspect 1 or aspect 2, wherein outputting the indication of the estimated location of the UE includes: sending the indication of the estimated location of the UE; or storing the indication of the estimated location of the UE.

[0219] Aspect 4 is the method according to any one of aspects 1 to 3, the method further comprising: sending a request for the visual feature list to the reference device before receiving the visual feature list.

[0220] Aspect 5 is the method according to any one of Aspects 1 to 4, wherein the location of the UE is at least one of the following: the relative location of the UE, the past location of the UE, the current location of the UE, or the estimated future location of the UE.

[0221] Aspect 6 is a method according to any one of aspects 1 to 5, wherein each visual feature in the list of visual features corresponds to an object in the environment, a portion of the object, or a characteristic of the object.

[0222] Aspect 7 is the method according to any one of Aspects 1 to 6, wherein the reference device includes a Global Navigation Satellite System (GNSS) module, at least one Inertial Measurement Unit (IMU), and one or more cameras, and wherein the six degrees of freedom (6DOF) of the reference device is convergent.

[0223] Aspect 8 is the method according to any one of Aspects 1 to 7, the method further comprising: receiving the 6DOF and real-time GNSS measurements of the reference device from the reference device.

[0224] Aspect 9 is a method according to any one of Aspects 1 to 8, wherein estimating the location of the UE based on at least one identified visual feature in the region and the location corresponding to the at least one visual feature comprises: initiating a 6DOF estimation process for a positioning engine based on the location corresponding to the at least one visual feature, the 6DOF of the reference device, and the real-time GNSS measurement; and calculating the location of the UE after the positioning engine converges.

[0225] Aspect 10 is a method according to any one of aspects 1 to 9, wherein receiving the visual feature list, the position of each visual feature in the visual feature list, the 6DOF of the reference device, and the real-time GNSS measurement comprises: receiving the visual feature list, the position of each visual feature in the visual feature list, the 6DOF of the reference device, and the real-time GNSS measurement via a broadcast message or a unicast message.

[0226] Aspect 11 is the method according to any one of aspects 1 to 10, wherein estimating the location of the UE comprises: estimating the location of the UE based on Visual Assisted Precision Positioning (VAPP).

[0227] Aspect 12 is the method according to any one of aspects 1 to 11, wherein the position corresponding to the at least one visual feature is a function of the six degrees of freedom (6DOF) of the at least one camera.

[0228] Aspect 13 is a method according to any one of aspects 1 to 12, wherein the visual feature list comprises a set of artificial features, and wherein the at least one visual feature comprises at least one artificial feature from the set of artificial features.

[0229] Aspect 14 is the method according to any one of aspects 1 to 13, wherein the set of artificial features corresponds to a set of laser projections.

[0230] Aspect 15 is a method according to any one of aspects 1 to 14, wherein the server is a map server or an environment server, and wherein the list of visual features is based on visual features presented in the map from the map server or the environment server.

[0231] Aspect 16 is a method according to any one of aspects 1 to 15, the method further comprising: obtaining a set of trajectory information of vehicles; and wherein estimating the location of the UE comprises: further estimating the location of the UE based on the trajectory information.

[0232] Aspect 17 is a method according to any one of aspects 1 to 16, the method further comprising: obtaining information associated with a Global Navigation Satellite System (GNSS) measurement error budget; and wherein estimating the positioning of the UE comprises: further estimating the positioning of the UE based on the information associated with the GNSS measurement error budget.

[0233] Aspect 18 is an apparatus for wireless communication at a user equipment (UE), the apparatus comprising: at least one memory; and at least one processor coupled to the at least one memory and based at least in part on information stored in the at least one memory, the at least one processor being configured individually or in any combination to implement any one of aspects 1 to 17.

[0234] Aspect 19 is the apparatus according to aspect 18, the apparatus further comprising at least one of a transceiver or an antenna coupled to the at least one processor.

[0235] Aspect 20 is an apparatus for wireless communication, the apparatus including components for implementing any one of aspects 1 to 17.

[0236] Aspect 21 is a computer-readable medium (e.g., a non-transitory computer-readable medium) storing computer-executable code, wherein the code, when executed by a processor, causes the processor to implement any one of aspects 1 to 17.

[0237] Aspect 22 is a method for wireless communication at a reference device, the method comprising: estimating the six degrees of freedom (6DOF) of the reference device; and transmitting a list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and a set of Global Navigation Satellite System (GNSS) measurements.

[0238] Aspect 23 is the method according to aspect 22, the method further comprising: receiving a request for the visual feature list from a user equipment (UE) before sending the visual feature list.

[0239] Aspect 24 is the method according to aspect 22 or aspect 23, wherein sending the visual feature list and the location of each visual feature in the visual feature list, the 6DOF of the reference device, and the set of GNSS measurements comprises: sending the visual feature list and the location of each visual feature in the visual feature list, the 6DOF of the reference device, and the set of GNSS measurements to the UE in response to the request.

[0240] Aspect 25 is a method according to any one of aspects 22 to 24, wherein each visual feature in the list of visual features corresponds to an object in the environment, a portion of the object, or a characteristic of the object.

[0241] Aspect 26 is the method according to any one of aspects 22 to 25, wherein the reference device includes a Global Navigation Satellite System (GNSS) module, at least one inertial measurement unit (IMU), and one or more cameras.

[0242] Aspect 27 is the method according to any one of aspects 22 to 26, wherein the 6DOF of the reference device is converged before transmitting the list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the set of GNSS measurements.

[0243] Aspect 28 is a method according to any one of aspects 22 to 27, wherein transmitting the list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the set of GNSS measurements comprises: transmitting the list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the set of GNSS measurements via broadcast or unicast messages.

[0244] Aspect 29 is the method according to any one of aspects 22 to 28, wherein the list of visual features includes a set of artificial features.

[0245] Aspect 30 is the method according to any one of aspects 22 to 29, wherein the set of artificial features corresponds to a set of light projections.

[0246] Aspect 31 is a method according to any one of aspects 22 to 30, the method further comprising: projecting at least one visual feature from the list of visual features via a projection module, or causing at least one projection device to project the at least one visual feature.

[0247] Aspect 32 is the method according to any one of aspects 22 to 31, wherein the reference device is associated with a local map database, a map server or an environment server, and wherein the list of visual features is based on visual features presented in a map from the map server or the environment server.

[0248] Aspect 33 is an apparatus for wireless communication at a reference device, the apparatus comprising: at least one memory; and at least one processor coupled to the at least one memory and based at least in part on information stored in the at least one memory, the at least one processor being configured individually or in any combination to implement any one of aspects 22 to 32.

[0249] Aspect 34 is the apparatus according to aspect 33, the apparatus further comprising at least one of a transceiver or an antenna coupled to the at least one processor.

[0250] Aspect 35 is a device for wireless communication, the device including components for implementing any one of aspects 22 to 32.

[0251] Aspect 36 is a computer-readable medium (e.g., a non-transitory computer-readable medium) that stores computer-executable code, wherein the code, when executed by a processor, causes the processor to implement any one of aspects 22 to 32.

Claims

1. An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: At least one memory; At least one transceiver; and At least one processor, coupled to the at least one memory and the at least one transceiver, wherein the at least one processor is configured individually or in any combination as follows: Receive a list of visual features and the location of each visual feature in the list from a reference device, server, or map; At least one visual feature in a region is identified via at least one camera, wherein the at least one visual feature is included in the list of visual features, and wherein the region is within a threshold distance of the UE; as well as The location of the UE is estimated based on at least one visual feature identified in the region and the location corresponding to the at least one visual feature.

2. The apparatus of claim 1, wherein the at least one processor is further configured, alone or in any combination, to: Output an indication of the estimated location of the UE.

3. The apparatus of claim 2, wherein, in order to output the indication of the estimated location of the UE, the at least one processor is configured individually or in any combination to: The indication of the estimated location of the UE is transmitted via the at least one transceiver; or The indication of the estimated location of the UE is stored.

4. The apparatus of claim 1, wherein the at least one processor is further configured, alone or in any combination, to: A request for the visual feature list is sent to the reference device before the visual feature list is received.

5. The apparatus of claim 1, wherein the positioning of the UE is at least one of the following: The relative positioning of the UE The UE's past location. The current location of the UE, or The estimated future location of the UE.

6. The apparatus of claim 1, wherein each visual feature in the list of visual features corresponds to an object in the environment, a portion of the object, or a characteristic of the object.

7. The apparatus of claim 1, wherein the reference device comprises a Global Navigation Satellite System (GNSS) module, at least one inertial measurement unit (IMU), and one or more cameras, and wherein the six degrees of freedom (6DOF) of the reference device are convergent.

8. The apparatus of claim 7, wherein the at least one processor is further configured, alone or in any combination, to: The 6DOF and real-time GNSS measurements of the reference device are received from the reference device via the at least one transceiver.

9. The apparatus of claim 8, wherein, in order to estimate the location of the UE based on at least one identified visual feature in the region and the location corresponding to the at least one visual feature, the at least one processor is configured individually or in any combination to: A 6DOF estimation process for the positioning engine is initiated based on the location corresponding to the at least one visual feature, the 6DOF of the reference device, and the real-time GNSS measurements; and The location of the UE is calculated after the positioning engine converges.

10. The apparatus of claim 8, wherein, in order to receive the list of visual features, the position of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement, the at least one processor is configured individually or in any combination to receive the list of visual features, the position of each visual feature in the list of visual features, the 6DOF of the reference device, and the real-time GNSS measurement via a broadcast message or a unicast message.

11. The apparatus of claim 1, wherein, in order to estimate the location of the UE, the at least one processor is configured individually or in any combination to estimate the location of the UE based on Visual Assisted Precise Localization (VAPP).

12. The apparatus of claim 1, wherein the position corresponding to the at least one visual feature is a function of the six degrees of freedom (6DOF) of the at least one camera.

13. The apparatus of claim 1, wherein the list of visual features comprises a set of artificial features, and wherein the at least one visual feature comprises at least one artificial feature from the set of artificial features.

14. The apparatus of claim 13, wherein the set of artificial features corresponds to a set of laser projections.

15. The apparatus of claim 1, wherein the server is a map server or an environment server, and wherein the list of visual features is based on visual features presented in the map from the map server or the environment server.

16. The apparatus of claim 1, wherein the at least one processor is further configured, individually or in any combination, to: Obtain trajectory information for a set of vehicles; and In order to estimate the location of the UE, the at least one processor is configured individually or in any combination to further estimate the location of the UE based on the trajectory information.

17. The apparatus of claim 1, wherein the at least one processor is further configured, individually or in any combination, to: Obtain information associated with the Global Navigation Satellite System (GNSS) measurement error budget; and In order to estimate the location of the UE, the at least one processor is configured individually or in any combination to further estimate the location of the UE based on the information associated with the GNSS measurement error budget.

18. A method for conducting wireless communication at a user equipment (UE), the method comprising: Receive a list of visual features and the location of each visual feature in the list from a reference device, server, or map; At least one visual feature in a region is identified via at least one camera, wherein the at least one visual feature is included in the list of visual features, and wherein the region is within a threshold distance of the UE; as well as The location of the UE is estimated based on at least one visual feature identified in the region and the location corresponding to the at least one visual feature.

19. An apparatus for wireless communication at a reference device, the apparatus comprising: At least one memory; At least one transceiver; and At least one processor, coupled to the at least one memory and the at least one transceiver, wherein the at least one processor is configured individually or in any combination as follows: Estimate the six degrees of freedom (6DOF) of the reference device; and The visual feature list and the location of each visual feature in the visual feature list, the 6DOF of the reference device, and a set of Global Navigation Satellite System (GNSS) measurements are transmitted via the at least one transceiver.

20. The apparatus of claim 19, wherein the at least one processor is further configured, alone or in any combination, to: A request for the visual feature list is received from the user equipment (UE) before the visual feature list is sent.

21. The apparatus of claim 20, wherein, in order to transmit the list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the set of GNSS measurements, the at least one processor is configured individually or in any combination to: transmit the list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the set of GNSS measurements to the UE in response to the request.

22. The apparatus of claim 19, wherein each visual feature in the list of visual features corresponds to an object in the environment, a portion of the object, or a characteristic of the object.

23. The apparatus of claim 19, wherein the reference device comprises a Global Navigation Satellite System (GNSS) module, at least one inertial measurement unit (IMU), and one or more cameras.

24. The apparatus of claim 19, wherein the 6DOF of the reference device is converged before transmitting the list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the set of GNSS measurements.

25. The apparatus of claim 19, wherein, in order to transmit the list of visual features and the location of each visual feature in the list of visual features, the 6DOF of the reference device, and the set of GNSS measurements, the at least one processor is configured individually or in any combination to: The list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and the set of GNSS measurements are transmitted via broadcast or unicast messages.

26. The apparatus of claim 19, wherein the list of visual features comprises a set of artificial features.

27. The apparatus of claim 26, wherein the set of artificial features corresponds to a set of light projections.

28. The apparatus of claim 26, wherein the at least one processor is further configured, alone or in any combination, to: At least one visual feature in the list of visual features is projected via a projection module, or at least one projection device is used to project the at least one visual feature.

29. The apparatus of claim 19, wherein the reference device is associated with a map server or an environment server, and wherein the list of visual features is based on visual features presented in a map from the map server or the environment server.

30. A method for wireless communication at a reference device, the method comprising: Estimate the six degrees of freedom (6DOF) of the reference device; as well as Send a list of visual features and the location of each visual feature in the list, the 6DOF of the reference device, and a set of Global Navigation Satellite System (GNSS) measurements.

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