Method and device for obtaining location information

Abstract

A method whereby a first device communicates wirelessly and a device supporting same are provided. For example, the first device may obtain a first unit of information related to a velocity vector of an entity, and a second unit of information related to an image of the entity. For example, the first device may obtain a third unit of information related to at least one of one or more local maximum points and one or more local minimum points related to the image of the entity, on the basis of the first and second units of information. For example, the first device may obtain a fourth unit of information related to a reference position of the entity on the basis of the third unit of information.

Description

Method and device for obtaining location information

[0001] The present disclosure relates to a wireless communication system.

[0002] 5G NR, the successor to LTE (long-term evolution), is a new clean-slate mobile communications system characterized by high performance, low latency, and high availability. 5G NR can utilize all available spectrum resources, from low-frequency bands below 1 GHz, mid-frequency bands between 1 GHz and 10 GHz, and high-frequency (millimeter wave) bands above 24 GHz.

[0003] The 6G (wireless communication) system aims to achieve (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) low energy consumption for battery-free Internet of Things (IoT) devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: intelligent connectivity, deep connectivity, holographic connectivity, and ubiquitous connectivity, and the 6G system can satisfy the requirements as shown in Table 1 below. For example, Table 1 can represent an example of the requirements of a 6G system.

[0004] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100bps / HzMobility supportUp to 1000km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0005] In one embodiment, a method for a first device to perform wireless communication is provided. For example, the first device may obtain first information related to a velocity vector of an entity and second information related to an image of the entity. For example, based on the first information and the second information, the first device may obtain third information related to at least one of one or more local maxima or one or more local minima related to the image of the entity. For example, based on the third information, the first device may obtain fourth information related to a reference position of the entity.

[0006] FIG. 1 illustrates a communication structure that can be provided in a 6G system according to one embodiment of the present disclosure.

[0007] FIG. 2 illustrates an electromagnetic spectrum according to one embodiment of the present disclosure.

[0008] FIG. 3 illustrates an example of a typical scenario of an NTN based on a transparent payload, according to one embodiment of the present disclosure.

[0009] FIG. 4 illustrates an example of a typical scenario of an NTN based on a regenerative payload, according to one embodiment of the present disclosure.

[0010] FIG. 5 illustrates an example of a sensing operation according to one embodiment of the present disclosure.

[0011] FIG. 6 is a diagram for explaining and comparing V2X communication based on RAT prior to NR and V2X communication based on NR according to one embodiment of the present disclosure.

[0012] FIG. 7 illustrates background removal and object segmentation according to one embodiment of the present disclosure.

[0013] FIG. 8 illustrates background removal and object segmentation according to one embodiment of the present disclosure.

[0014] FIG. 9 illustrates a method for obtaining a motion vector based on a differential image according to an embodiment of the present disclosure.

[0015] FIG. 10 illustrates a method for obtaining a motion vector based on a differential image according to an embodiment of the present disclosure.

[0016] FIG. 11 illustrates a method for obtaining a motion vector according to an embodiment of the present disclosure.

[0017] FIG. 12 illustrates a method for obtaining a motion vector according to an embodiment of the present disclosure.

[0018] FIG. 13 illustrates a method for obtaining a motion vector according to an embodiment of the present disclosure.

[0019] FIG. 14 illustrates a method for obtaining a motion vector based on a differential image according to an embodiment of the present disclosure.

[0020] FIG. 15 illustrates a method for obtaining a motion vector based on a differential image according to an embodiment of the present disclosure.

[0021] FIG. 16 illustrates a method for obtaining a motion vector based on a differential image according to an embodiment of the present disclosure.

[0022] FIG. 17 illustrates a method for obtaining a reference position based on a differential image according to an embodiment of the present disclosure.

[0023] FIG. 18 illustrates a method for obtaining a reference position based on a differential image according to one embodiment of the present disclosure.

[0024] FIG. 19 illustrates a method for obtaining a reference position based on a differential image according to an embodiment of the present disclosure.

[0025] FIG. 20 illustrates a procedure for obtaining a reference position according to one embodiment of the present disclosure.

[0026] FIG. 21 illustrates a method for obtaining the length of an object according to one embodiment of the present disclosure.

[0027] FIG. 22 illustrates a method for obtaining the length of an object according to one embodiment of the present disclosure.

[0028] FIG. 23 illustrates a method for obtaining location information according to one embodiment of the present disclosure.

[0029] FIG. 24 illustrates a method for a first device to perform wireless communication according to one embodiment of the present disclosure.

[0030] Fig. 25 shows a communication system (1) according to one embodiment of the present disclosure.

[0031] FIG. 26 illustrates a wireless device according to one embodiment of the present disclosure.

[0032] FIG. 27 illustrates a signal processing circuit for a transmission signal according to one embodiment of the present disclosure.

[0033] FIG. 28 illustrates a wireless device according to one embodiment of the present disclosure.

[0034] FIG. 29 illustrates a mobile device according to one embodiment of the present disclosure.

[0035] FIG. 30 illustrates a vehicle or autonomous vehicle according to one embodiment of the present disclosure.

[0036] As used herein, "A or B" can mean "only A," "only B," or "both A and B." In other words, as used herein, "A or B" can be interpreted as "A and / or B." For example, as used herein, "A, B or C" can mean "only A," "only B," "only C," or "any combination of A, B and C."

[0037] As used herein, a slash ( / ) or a comma can mean "and / or." For example, "A / B" can mean "A and / or B." Accordingly, "A / B" can mean "only A," "only B," or "both A and B." For example, "A, B, C" can mean "A, B, or C."

[0038] In this specification, "at least one of A and B" may mean "only A", "only B" or "both A and B". Additionally, in this specification, the expressions "at least one of A or B" or "at least one of A and / or B" may be interpreted identically to "at least one of A and B".

[0039] Additionally, in this specification, “at least one of A, B and C” can mean “only A,” “only B,” “only C,” or “any combination of A, B and C.” Additionally, “at least one of A, B or C” or “at least one of A, B and / or C” can mean “at least one of A, B and C.”

[0040] Additionally, parentheses used herein may mean "for example." Specifically, when indicated as "control information (PDCCH)", "PDCCH" may be proposed as an example of "control information." In other words, "control information" in this specification is not limited to "PDCCH," and "PDCCH" may be proposed as an example of "control information." Furthermore, even when indicated as "control information (i.e., PDCCH)", "PDCCH" may be proposed as an example of "control information."

[0041] In the following explanation, ‘when, if, in case of’ can be replaced with ‘based on’.

[0042] Technical features individually described in a single drawing in this specification may be implemented individually or simultaneously.

[0043] In this specification, higher layer parameters may be parameters that are set for the terminal, preset, or predefined. For example, a base station or network may transmit higher layer parameters to the terminal. For example, higher layer parameters may be transmitted via radio resource control (RRC) signaling or medium access control (MAC) signaling.

[0044] In this specification, "configured or defined" may be interpreted as being configured or preset to a device through predefined signaling (e.g., SIB, MAC, RRC) from a base station or network. In this specification, "configured or defined" may be interpreted as being preset to a device.

[0045] The technology proposed in this specification can be used in various wireless communication systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access). CDMA can be implemented with wireless technologies such as UTRA (universal terrestrial radio access) or CDMA2000. TDMA can be implemented with wireless technologies such as GSM (global system for mobile communications) / GPRS (general packet radio service) / EDGE (enhanced data rates for GSM evolution). OFDMA can be implemented with wireless technologies such as IEEE (Institute of Electrical and Electronics Engineers) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, E-UTRA (evolved UTRA), LTE (long term evolution), and 5G NR.

[0046] The technology proposed in this specification can be implemented with 6G wireless technology and applied to various 6G systems. For example, 6G systems can have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine-type communication (mMTC), artificial intelligence (AI) integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0047] FIG. 1 illustrates a communication structure that can be provided in a 6G system according to one embodiment of the present disclosure. The embodiment of FIG. 1 can be combined with various embodiments of the present disclosure.

[0048] New network characteristics in 6G may include:

[0049] - Satellite integrated network

[0050] - Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is revolutionary, upgrading the wireless evolution from "connected objects" to "connected intelligence." AI can be applied at every stage of the communication process (or at every signal processing step, as described below).

[0051] - Seamless integration of wireless information and energy transfer

[0052] - Ubiquitous super 3D connectivity: Access to networks and core network functions of drones and very low Earth orbit satellites will create super 3D connectivity in 6G ubiquitous.

[0053] Some general requirements for the new network characteristics of 6G, such as the above, may be as follows:

[0054] - small cell networks

[0055] - Ultra-dense heterogeneous network

[0056] - High-capacity backhaul

[0057] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communications is a key feature of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0058] - Softwarization and virtualization

[0059] Below, the core implementation technologies of the 6G system are described.

[0060] - Artificial Intelligence: Incorporating AI into communications can streamline and improve real-time data transmission. AI can use numerous analytics to determine how complex target tasks should be performed. This means AI can increase efficiency and reduce processing delays. Time-consuming tasks such as handovers, network selection, and resource scheduling can be performed instantly using AI. AI can also play a crucial role in machine-to-machine (M2M), machine-to-human, and human-to-machine communications. Furthermore, AI can facilitate rapid communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0061] - THz communication (terahertz communication): Data rates can be increased by increasing the bandwidth. This can be achieved by utilizing sub-THz communication with a wide bandwidth and applying advanced massive MIMO technology. THz waves, also known as sub-millimeter waves, typically refer to the frequency range between 0.1 THz and 10 THz with corresponding wavelengths ranging from 0.03 mm to 3 mm. The 100 GHz to 300 GHz band (Sub-THz band) is considered a major portion of the THz band for cellular communications. Adding the Sub-THz band to the mmWave band will increase the capacity of 6G cellular communications. Among the defined THz bands, 300 GHz to 3 THz lies in the far infrared (IR) frequency band. While part of the optical band, the 300 GHz to 3 THz band lies at the boundary of the optical band, immediately following the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF. Figure 2 illustrates the electromagnetic spectrum according to one embodiment of the present disclosure. The embodiment of FIG. 2 can be combined with various embodiments of the present disclosure. Key characteristics of THz communications include (i) a widely available bandwidth to support very high data rates, and (ii) high path loss at high frequencies (highly directional antennas are essential). The narrow beamwidth generated by the highly directional antenna reduces interference. The small wavelength of THz signals allows for a much larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array technologies to overcome range limitations.

[0062] - Large-scale MIMO technology

[0063] - Hologram beamforming (HBF)

[0064] - Optical wireless technology

[0065] - Free-space optical transmission backhaul network (FSO backhaul network)

[0066] - Quantum communication

[0067] - Cell-free communication

[0068] - Integration of wireless information and power transmission

[0069] - Integration of wireless communication and sensing

[0070] - Integrated access and backhaul network

[0071] - Big data analysis

[0072] - Reconfigurable intelligent surface

[0073] - metaverse

[0074] - Blockchain

[0075] Unmanned aerial vehicles (UAVs): UAVs, or drones, will be a key element in 6G wireless communications. In most cases, high-speed data wireless connectivity can be provided using UAV technology. Base stations (BSs) can be installed on UAVs to provide cellular connectivity. UAVs may offer specific capabilities not found in fixed BS infrastructure, such as easy deployment, robust line-of-sight links, and controlled mobility. During emergencies such as natural disasters, deploying terrestrial communications infrastructure is not economically feasible and sometimes cannot provide services in volatile environments. UAVs can easily handle these situations. UAVs will become a new paradigm in wireless communications. This technology facilitates three fundamental requirements for wireless networks: enhanced mobile broadband (eMBB), URLLC, and mMTC. UAVs can also support various purposes, such as enhancing network connectivity, fire detection, disaster emergency services, security and surveillance, pollution monitoring, parking monitoring, and accident monitoring. Therefore, UAV technology is recognized as one of the most important technologies for 6G communications.

[0076] - Advanced air mobility (AAM): AAM is a higher concept than urban air mobility (UAM), which is an air transportation method available in urban areas, and can refer to a means of transportation that includes movement between regional hubs as well as within urban areas.

[0077] - Autonomous driving (self-driving): V2X (vehicle to everything), a key element in building autonomous driving infrastructure, can be a technology that allows cars to communicate and share with various elements on the road for autonomous driving, such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communication. Fast transmission speeds and low-latency technologies are essential to maximize autonomous driving performance and ensure high safety. Furthermore, in the future, autonomous driving will go beyond simply providing warnings or guidance messages to drivers and may require active intervention in vehicle operation and direct control of the vehicle in dangerous situations. To this end, the amount of information that needs to be transmitted and received may become enormous, so 6G is expected to maximize autonomous driving with faster transmission speeds and lower latency than 5G.

[0078] - Non-terrestrial networks (NTN): NTN may refer to a network or network segment that uses radio frequency (RF) resources mounted on a satellite (or unmanned aerial system (UAS) platform). FIG. 3 illustrates an example of a typical NTN scenario based on a transparent payload according to an embodiment of the present disclosure. FIG. 4 illustrates an example of a typical NTN scenario based on a regenerative payload according to an embodiment of the present disclosure. The embodiments of FIG. 3 or FIG. 4 may be combined with various embodiments of the present disclosure. Referring to FIG. 3, a satellite (or UAS platform) may create a service link with a UE. The satellite (or UAS platform) may be connected to a gateway via a feeder link. The satellite may be connected to a data network via the gateway. A beam footprint may refer to an area where a signal transmitted by a satellite can be received. Referring to Figure 4, a satellite (or UAS platform) can establish a service link with a UE. A satellite (or UAS platform) connected to a UE can be connected to another satellite (or UAS platform) via an inter-satellite link (ISL). The other satellite (or UAS platform) can be connected to a gateway via a feeder link. Based on the playback payload, a satellite can be connected to a data network through another satellite and the gateway. If an ISL does not exist between a satellite and another satellite, a feeder link between the satellite and the gateway may be required. Figures 3 and 4 are merely examples of NTN scenarios, and NTN can be implemented based on various scenarios.For example, a satellite (or UAS platform) may implement a transparent or regenerative (with onboard processing) payload. For example, a satellite (or UAS platform) may generate multiple beams over a designated service area depending on the field of view of the satellite (or UAS platform). For example, the field of view of the satellite (or UAS platform) may vary depending on the onboard antenna diagram and minimum elevation angle. For example, a transparent payload may include radio frequency filtering, frequency conversion, and amplification. Therefore, the waveform signal repeated by the payload may not be altered. For example, a regenerative payload may include radio frequency filtering, frequency conversion and amplification, demodulation / decoding, switching and / or routing, and coding / modulation. For example, a regenerative payload may be substantially equivalent to equipping the satellite (or UAS platform) with all or part of the base station functionality.

[0079] - Integrated Sensing and Communication (ISAC): Wireless sensing is a technology that uses radio frequencies to determine the instantaneous linear velocity, angle, distance (range), etc. of an object, thereby obtaining information about the characteristics of the environment and / or objects within the environment. Because radio frequency sensing does not require a device to connect to the object through a network, it can provide a service for object positioning without a device. The ability to obtain range, velocity, and angle information from radio frequency signals can enable a wide range of new capabilities, such as various object detection, object recognition (e.g., vehicles, humans, animals, UAVs), and high-precision localization, tracking, and activity recognition. Wireless sensing services can provide information to a variety of industries (e.g., drones, smart homes, V2X, factories, railways, public safety, etc.), enabling applications such as intruder detection, assisted vehicle steering and navigation, trajectory tracking, collision avoidance, traffic management, and health and traffic management. In some cases, wireless sensing can utilize non-3GPP type sensors (e.g., radar, cameras) to further support 3GPP-based sensing. For example, the operation of a wireless sensing service, i.e., a sensing operation, may depend on the transmission, reflection, and scattering of wireless sensing signals. Therefore, wireless sensing may provide an opportunity to enhance existing communication systems from a communication network to a wireless communication and sensing network. FIG. 5 illustrates an example of a sensing operation according to an embodiment of the present disclosure. The embodiment of FIG. 5 may be combined with various embodiments of the present disclosure. Specifically, FIG. 5 (a) illustrates an example of sensing using a sensing receiver and a sensing transmitter located at the same location (e.g., monostatic sensing), and FIG. 5 (b) illustrates an example of sensing using a separated sensing receiver and a sensing transmitter (e.g., bistatic sensing).

[0080] FIG. 6 is a diagram for comparing and explaining V2X communication based on RAT prior to NR and V2X communication based on NR. The embodiment of FIG. 6 can be combined with various embodiments of the present disclosure.

[0081] In relation to V2X communication, in RATs prior to NR, methods for providing safety services based on V2X messages such as Basic Safety Message (BSM), Cooperative Awareness Message (CAM), and Decentralized Environmental Notification Message (DENM) were mainly discussed. V2X messages may include location information, dynamic information, attribute information, etc. For example, a terminal may transmit a CAM of a periodic message type and / or a DENM of an event triggered message type to another terminal.

[0082] For example, a CAM may include basic vehicle information such as dynamic vehicle status information, such as direction and speed, static vehicle data, such as dimensions, external lighting conditions, and route history. For example, a terminal may broadcast a CAM, and the latency of the CAM may be less than 100 ms. For example, in the event of an emergency, such as a vehicle breakdown or accident, a terminal may generate a DENM and transmit it to other terminals. For example, all vehicles within the transmission range of the terminal may receive the CAM and / or DENM. In this case, the DENM may have a higher priority than the CAM.

[0083] Since then, various V2X scenarios have been proposed in NR in relation to V2X communications. For example, various V2X scenarios may include vehicle platooning, advanced driving, extended sensors, and remote driving.

[0084] For example, based on vehicle platooning, vehicles can dynamically form groups and move together. For example, to perform platoon operations based on vehicle platooning, vehicles in the group can receive periodic data from the lead vehicle. For example, vehicles in the group can use this periodic data to narrow or widen the gap between vehicles.

[0085] For example, based on improved driving, vehicles can become semi-autonomous or fully automated. For example, each vehicle can adjust its trajectories or maneuvers based on data acquired from local sensors of nearby vehicles and / or nearby logical entities. Furthermore, for example, each vehicle can share driving intentions with nearby vehicles.

[0086] For example, based on extended sensors, raw data, processed data, or live video data acquired through local sensors can be exchanged between vehicles, logical entities, pedestrian terminals, and / or V2X application servers. Thus, for example, a vehicle can perceive its environment better than it can perceive using its own sensors.

[0087] For example, based on remote driving, a remote driver or V2X application can operate or control the remote vehicle for people who cannot drive or for remote vehicles located in hazardous environments. For example, in cases where the route is predictable, such as public transportation, cloud computing-based driving can be utilized to operate or control the remote vehicle. Additionally, access to a cloud-based back-end service platform, for example, can be considered for remote driving.

[0088] Meanwhile, a method to specify service requirements for various V2X scenarios, such as vehicle platooning, enhanced driving, expanded sensors, and remote driving, is being discussed in NR-based V2X communication.

[0089] The present disclosure may relate to a method for setting a reference position of an object detected by a camera. According to one embodiment of the present disclosure, when the absolute position of each pixel of an image captured by a camera or the relative position from a specific reference point (e.g., camera installation position) is known, when detecting an object by a camera, the reference position may be simply derived from a bounding box generated during object detection. For example, if the midpoint of the bounding box is determined as the reference point, it may be inaccurate for an object occupying a three-dimensional space. For example, when the width and length (e.g., x-axis and y-axis values) are very small, the center of the bounding box may be a value close to a 3D position value indicating a position corresponding to half the height, and the center point of the area corresponding to the ground level of the bounding box (e.g., may be a combination of x-axis and y-axis values) may be a value close to the ground level corresponding to the location of the actual object, and there may be no problem in setting it as the reference point. However, among the actual detected objects, for example, there may be not only road users with a small surface area, such as pedestrians, but also objects with a large surface area and three-dimensional shape, such as passenger cars or large buses, and the simple reference point determination method described above may not be able to determine an accurate reference point.

[0090] According to one embodiment of the present disclosure, when a reference point is determined based on the bounding box, the reference point may change due to changes in the size and / or position of the bounding box. For example, since the reference point is changed due to changes in the size and / or position of the bounding box, there may be cases where information such as the speed and heading of a specific object are derived regardless of the original values, direction, etc. In addition, for example, when a simple reference point determination method such as the above is applied when an object is not fully displayed on the screen, a bounding box may be generated based only on the shape revealed on the screen, which may further increase the error value.

[0091] According to one embodiment of the present disclosure, if a reference point is set using only a bounding box generated for object detection (e.g., as described above), not only may the error in the reference point increase, but the derived speed, heading value, etc. may be calculated incorrectly as a result, and this may cause errors when generating a safety message and generating a related notification using the detection result value. For example, to prevent such problems, a more stable method than a bounding box-based reference point setting method may be required.

[0092] According to one embodiment of the present disclosure, in image processing and / or artificial intelligence-based object detection, generating a bounding box for an object expresses a minimum boundary for the possibility of the object's existence, and an additional process may be required to indicate the actual location of the object. For example, in the case of a camera image, a three-dimensional (3D) object, such as a person or a car, is projected onto a 2D area of ​​a camera sensor and output, and the actual location of a specific pixel of a specific object in the real world / space may be one of the 3D coordinate values ​​due to the three-dimensional characteristics of the object, or may be determined as a single 2D coordinate value that satisfies a specific criterion (e.g., coordinate value of the z-axis = 0 or the ground level, etc.).

[0093] At this time, according to one embodiment of the present disclosure, if all components of an object included in a bounding box correspond to 2D coordinate values, it is only necessary to determine which part of the object is to be set as a reference point, and by obtaining the 2D coordinate value for the corresponding point, the location of the reference point can be known.

[0094] Additionally, according to one embodiment of the present disclosure, the bounding box may be generated over a wider area than the actual object, or may be generated by detecting only a portion of the object (e.g., occlusion, or when the object begins to enter the camera's field of view).

[0095] Therefore, according to one embodiment of the present disclosure, in order to determine a reference point for an object having a three-dimensional feature (as described above) and / or of which some areas may not be detected, it may be more appropriate to process with a focus on a 2D area rather than a three-dimensional portion, and it may be necessary to enable processing using only the exposed portion.

[0096] FIG. 7 illustrates background removal and object segmentation according to an embodiment of the present disclosure. The embodiment of FIG. 7 can be combined with various embodiments of the present disclosure.

[0097] Referring to FIG. 7, according to one embodiment of the present disclosure, when detecting a mobile object, changes in the image may be reflected and revealed according to the movement of the object. Therefore, for example, even with only a background removal technique (e.g., as shown in FIGS. 7 and 8), an object segmentation range that distinguishes an area actually occupied by an object can be extracted very accurately. For example, in the background removal technique of the present disclosure, an image may be captured for a certain period of time, a part where motion temporarily occurs may be filtered out from the image, and only an actually still image may be generated as a background, and / or a part that is different from the background may be masked and detected, thereby detecting an object newly generated from the background or detecting and tracking a mobile object. For example, during this object segmentation process, a phenomenon in which a part of the object is removed together with the background may occur. In this case, for example, operations such as connecting and filling in pixels removed through morphological transformation for correction (e.g. dilation) can be performed.

[0098] According to one embodiment of the present disclosure, since object segmentation covers a more precise area than a bounding box, if both object segmentation and bounding box generation are performed accurately, the bounding box may include the object segmentation area. Therefore, for example, the bounding box can be used as a type of upper bound, and errors that may occur in the process of detecting and tracking an object through background removal, object segmentation, etc. can be limited and eliminated. For example, if the image processing / AI-based object detection is accurate with a detection rate of d1 % or higher (e.g., d1=90%), it can be seen that the bounding box sufficiently limits the range of the object, and thus the reference point of the detected object can be limited to being acquired only within the bounding box area. For example, more specifically, if the object segmentation area (i.e. segment) is not completely contained in the bounding box, the image for the object can be processed only for the overlapping area (intersection) of the bounding box and the segment. However, if the image processing / AI-based object detection is not accurate, for example, with a detection rate of d2 % or less (e.g. d2 = 70%), the bounding box cannot be considered to have sufficiently limited the range of the object, and in this case, the object segmentation result can be used preferentially.For example, more specifically, if the object segmentation region (i.e. segment) is not completely contained in the bounding box, additional image processing for the object can be performed only on the object segmentation region or on the entire region (union) of the bounding box and the segment.

[0099] FIG. 8 illustrates background removal and object segmentation according to an embodiment of the present disclosure. The embodiment of FIG. 8 may be combined with various embodiments of the present disclosure.

[0100] Referring to FIG. 8, according to one embodiment of the present disclosure, since additional image processing methods such as the background removal method may result in increased computational load, burden on processing power, etc., in order to prevent additional image processing methods such as the background removal method, in a situation where bounding box acquisition is performed first (e.g., as in FIG. 8), the bounding box area may be derived first, and then the background removal, object segmentation, etc. may be performed only within the bounding box areas. In this case, for example, it may be performed only for the accurately detected bounding box (e.g., detection rate d1=90% or higher), and in order to check whether any objects are missed in the remaining areas, background removal, object segmentation, etc. may be performed periodically or intermittently in an area excluding the bounding box area. For example, the operation(s) of the present disclosure may be equally applied to the remaining methods below.

[0101] FIGS. 9 and 10 illustrate a method for obtaining a motion vector based on a differential image, according to an embodiment of the present disclosure. The embodiments of FIGS. 9 and / or 10 may be combined with various embodiments of the present disclosure.

[0102] Referring to FIGS. 9 and / or 10, according to an embodiment of the present disclosure, when object segmentation is performed based on the background removal method, etc., image information on a mobile object can be obtained. At this time, for example, mobility information can also be obtained by tracking changes in the image information. For example, a motion vector of an object can be obtained by tracking certain pixels by comparing the previous image(s) with the current image. At this time, for example, when tracking the object segmented image and displaying only newly generated pixels, if a surface in contact with the direction of movement is revealed to the camera, for example, when moving toward the camera, pixels that have moved in the direction of movement can be extracted as is. Also, for example, if the surface in contact with the direction of travel is not visible to the camera but is covered or turned away, pixels that have traveled in the direction of travel cannot be derived. In this case, instead of tracking newly generated pixels (e.g., as described above), pixels that existed previously but have disappeared can be tracked.

[0103] According to one embodiment of the present disclosure, the image components for the surface in contact with the direction of travel (i.e., the direction of travel plane / cross section / bottom plane, ...) can be obtained from the difference images, more specifically, from the difference image (i.e., difference image 1) that tracks newly generated pixels (e.g., as in FIG. 9), or from the difference image (i.e., difference image 2) that tracks disappeared pixels (e.g., as in FIG. 10), the image components for the back of the surface in contact with the direction of travel can be obtained. For example, at least one component related to the direction of travel can be obtained from difference image 1 and difference image 2. More specifically, as an example, the coordinates of the point (i.e., the extreme value (maximum value, minimum value) 1) closest to the camera in difference image 1 and the coordinates of the point (i.e., the extreme value (maximum value, minimum value) 2) closest to the camera in difference image 2 can be compared, and the coordinate values ​​of the closer point can be set as the extreme value (maximum value, minimum value). For example, if the extremum (maximum value, minimum value) 1 is determined as an extremum (maximum value, minimum value), it can be determined that the object is moving in a direction approaching the camera, and the reference point can be determined based on the front direction of the object. Conversely, for example, if the extremum (maximum value, minimum value) 2 is determined as an extremum (maximum value, minimum value), it can be determined that the object is moving in a direction away from the camera, and the reference point can be determined based on the rear direction of the object. In addition, for example, a method of tracking a certain pixel(s) can be used to obtain a motion vector (e.g., as mentioned above). In this case, for example, the motion vector for the direction of movement can be obtained only by tracking the components related to the above-mentioned progress plane, or at least the obtained extremum values ​​(maximum value, minimum value).

[0104] FIGS. 11, 12, and 13 illustrate a method for obtaining a motion vector according to an embodiment of the present disclosure. The embodiments of FIGS. 11, 12, and / or 13 may be combined with various embodiments of the present disclosure.

[0105] Referring to FIGS. 11, 12, and / or 13, according to an embodiment of the present disclosure, since the point related to the reference point setting among the progress plane components can be accurately acquired from the 2D component, it can be acquired from a point close to the ground level, i.e., pixels close to the camera. For example, more specifically, a point with the smallest y value on the progress plane or a point corresponding to half the width (if the width is exactly revealed in the progress wavefront) based on the point where the progress plane starts can be designated (e.g., FIGS. 11, 12), or, for example, if the specifications can be estimated through information such as the type or specific model (e.g., a specific product of a specific manufacturer) of the detected object, the width can be estimated to designate the position of the center point (e.g., approximately 2 m wide in the case of a sedan). For example, if the progress plane does not appear to be in the form of a straight line or appears in an irregular form, the point where the normal component of the progress motion vector touches (i.e., the point where a large-area object may first come into contact in the corresponding direction) can be designated as the center point or a point associated with the reference point (i.e., the heading reference point) (e.g., Fig. 13).

[0106] FIGS. 14, 15, and 16 illustrate a method for obtaining a motion vector based on a differential image, according to an embodiment of the present disclosure. The embodiments of FIGS. 14, 15, and / or 16 may be combined with various embodiments of the present disclosure.

[0107] Referring to FIGS. 14, 15, and / or 16, according to an embodiment of the present disclosure, the motion vector may not be obtained directly from the image plane on which the image of the camera is mapped, but may be obtained by the difference in values ​​of coordinates corresponding to the pixels of the image in the actual real world / space. For example, more specifically, an operation using a mapping table or transformation matrix for the actual GNSS (Global Navigation Satellite System) coordinates indicated by each pixel may be required. For example, in the case of a plane on which the image of the camera is captured, it may be depicted by a method such as perspective transformation (e.g., as in FIG. 14). For example, if objects of the same size appear smaller the farther away they are, parallel straight lines in the real world / space will converge to meet at a single vanishing point in the image plane, and the shape of a straight line in the real world / space will also appear as a straight line in the image plane. For example, the corresponding transformation matrix can be expressed as M, and in order to minimize the number of coefficients that must be found when converting from the real world / space to the image plane and to simplify the formula, in both cases (e.g., as in Figs. 15 and 16), the minimum value of the y-axis can be 0, and it can be expressed as a shape that is symmetrical around the origin. (For example, by taking into account the relative distance, etc., the actual GNSS (Global Navigation Satellite System) coordinates, etc. can be found.) For example, a trapezoidal plane with vertices of (-x1, y0), (-x0, 0), (x0, 0), (x1, y0) in the real world / space can be expressed in the form of (-x0, x0 / a), (-x0, 0), (x0, 0), (x0, x0 / a) in the image plane. (For example, a means the width:height ratio of a rectangle when four points of the real world / space are converted into the form of four corners of a rectangle of an image plane, and means the aspect ratio of an image sensor or display when four points of the real world / space fill the entire area of ​​the image plane.) At this time, for example, the transformation matrix M can be expressed as in mathematical expression 1, and the coefficients can be as in mathematical expression 2 below.

[0108]

[0109]

[0110] FIGS. 17, 18, and 19 illustrate a method for obtaining a reference position based on a differential image, according to an embodiment of the present disclosure. The embodiments of FIGS. 17, 18, and / or 19 may be combined with various embodiments of the present disclosure.

[0111] Referring to FIG. 17, FIG. 18, and / or FIG. 19, according to one embodiment of the present disclosure, the extremum (maximum, minimum) and the motion vector can be obtained, and in a given situation where a differential image (an image related to a progress plane) related to the derivation of the extremum (maximum, minimum) is provided, the differential image in the image plane can be transformed into a real world / space coordinate system to set a reference point or derive a value related thereto.

[0112] According to one embodiment of the present disclosure, when the differential image is V1 as in FIG. 20 and the image converted to the real world / space coordinate system as in FIG. 18 is V1', for example, the amount of change in the extreme values ​​(maximum values, minimum values) at time t2 and time t1 (or the value obtained by analytically / statistically processing the amount of change in the extreme values ​​(maximum values, minimum values) at time t2 and time t1) can be expressed as a motion vector at time t2, and the V1' image (e.g., of FIG. 21) may be in a form that is rotated by an amount corresponding to this motion vector M1' (e.g., by θ with respect to the x-axis) based on the GNSS (Global Navigation Satellite System) orthogonal coordinate system or the x-axis, y-axis orthogonal coordinate system. Therefore, for example, in order to directly derive the extreme values ​​(maximum values, minimum values) in the real world / space, the object can be derived by rotating it by -90 degrees or 270 degrees with respect to the x-axis (e.g., expressing a curve in the shape of a convex downwards), so it can be derived by additionally rotating it by (-90-θ) as in the R matrix below from the current state, and for example, it can be derived by applying a rotation transformation as in the following mathematical expression 3 to V1'.

[0113]

[0114] According to one embodiment of the present disclosure, for example, the final transformed image V1” can be expressed by mathematical expression 4.

[0115]

[0116] Among the coordinates indicated by the above V1”, the extreme value (maximum value, minimum value) (the point with the minimum y value) may be the point where there is a possibility of collision on the object’s progress plane when colliding with another object. In this case, as an example, M expressed above -1*V1 operation is M -1 *It can mean that only two components corresponding to the x and y coordinates are extracted and operated from the result value of the V1 operation, and the remaining components can be used only as normalization factors to normalize the x and y component values ​​derived above. For example, M -1 *V1” can be obtained by performing rotation transformation by R on the result of V1 operation. For example, if the extremum (maximum value, minimum value) obtained from the above V1” is L1, in order to express it as a GNSS (Global Navigation Satellite System) coordinate value of the real world / space, the L1 value is converted to R. -1 *It can be converted and used like L1, and the actual GNSS (Global Navigation Satellite System) coordinates can be obtained by considering relative distances, etc. from the converted values, and a reference point can be set from the GNSS coordinates.

[0117] According to one embodiment of the present disclosure, if the extrema (maxima, minima) derived from the V1 image are tracking the same point well, the M1” derived from the image and the motion vector M2” newly derived by the extrema (maxima, minima) obtained by the V1” image in FIG. 22 may have the same vector value. For example, if M1” / M2” have different values, the newly derived M2” value may be given priority.

[0118] According to one embodiment of the present disclosure, if an image of a progress plane / cross-section, etc. is clearly derived from the differential image, or if the width of an object, etc. can be derived accurately (or approximately), a reference point can be sufficiently derived in the image plane without going through real world / space coordinate transformation, etc.

[0119] According to one embodiment of the present disclosure, for example, the extremum (maximum value, minimum value) (A1=(x A ,y A )) and a motion vector are derived, in a case where the width component of the object is clearly revealed (e.g., as in Fig. 11 and Fig. 12), the distance from the extreme value (maximum value, minimum value) to the opposite side of the extreme value (maximum value, minimum value), for example, when the front is detected, the distance to the vertex which is the maximum value or minimum value of the x-axis in the differential image in the direction of the motion vector, or conversely, when the rear is detected, the distance to the vertex which is the maximum value or minimum value of the x-axis in the differential image in the opposite direction of the motion vector, may be the width of the object. For example, the actual GNSS (Global Navigation Satellite System) coordinates (or the M -1 The center point of the transformed point through the matrix can be set as the reference point.

[0120] According to one embodiment of the present disclosure, or (e.g., in the case of FIG. 13), the point where the difference image and the vector perpendicular to the motion vector meet can be expressed as a component corresponding to the vertex, and the vector VM1 perpendicular to the motion vector can be derived as in the following mathematical expression 5. For example, here, M1 can represent the motion vector. For example, another point other than the local minimum A1 constituting the M1 vector (e.g., the starting point of the M1 vector) B1 = (x B , y B ) can be expressed as follows. For example, the above method can be applied even when the above A1 is not an actual minimum value.

[0121]

[0122] According to one embodiment of the present disclosure, the point where VM1 is translated in parallel and intersects with the differential image may be set as a reference point. Alternatively, the point where the differential image intersects with a straight line extending from A1 in the direction of VM1 may be a point corresponding to the vertex. Alternatively, the extreme value (maximum value, minimum value) and the midpoint of this vertex may be simply set as a reference point, or another vertex where the motion vector originating from this midpoint intersects with the differential image may be set as a reference point.

[0123] According to one embodiment of the present disclosure, a method of determining a reference point using only a bounding box is based on the amount of change in the image of a mobile object, and may cause errors or may not move for stationary objects. For example, this may occur in object segmentation through background removal, but if a motion vector is not obtained in the relevant area, or the velocity value is 0, or if an image indicating mobility does not occur in the difference image, the object may be determined to be stationary, and the state of the object may be designated as stationary, and tracking may be performed to determine whether motion occurs thereafter. Alternatively, for example, if an object that previously existed suddenly does not appear through background removal or object segmentation, it can be determined that there is an occlusion situation, and if a related V2X message can be obtained from the object or from another road user / infra(structure) in the vicinity (e.g., RSU (Road Side Unit) proxy / proximity V2X message), tracking can be performed using information from the existing detection results and / or at least one of the V2X messages.

[0124] FIG. 20 illustrates a procedure for obtaining a reference position according to an embodiment of the present disclosure. The embodiment of FIG. 20 may be combined with various embodiments of the present disclosure.

[0125] Referring to FIG. 20, according to one embodiment of the present disclosure, a point associated with a reference point or a heading direction reference point can be obtained through the object detection and additional image processing (e.g., FIG. 20). In this case, for example, if the heading direction reference point faces the direction of travel (forward in the case of a straight-going vehicle), it can be called an entry reference point, and if it faces in the direction opposite to the direction of travel (e.g. (e.g. backward in the case of a straight-going vehicle)), it can be called an exit reference point. For example, a reference point corresponding to the center of an object can be called a center reference point.

[0126] According to one embodiment of the present disclosure, in the case of the entry reference point, the traveling wavefront that touches the reference point may be suitable for use as a reference point in estimating the possibility of collision with actual surrounding objects, etc. For example, if the entry reference point can always be used as a reference point for positioning a V2X message, the initial detection result alone may be sufficient to quickly determine the position reference point even when the object has only partially entered without special consideration of the length of the vehicle, etc., or when the rear is obscured or has just started to emerge from an obstacle. However, since the entry reference point may not be visible or cannot be accurately located depending on the camera angle, the direction of travel, etc., the entry reference point cannot always be used. Therefore, for example, there may be cases where the exit reference point must be used instead of the entry reference point.

[0127] According to one embodiment of the present disclosure, in the case of the above-mentioned exit reference point, the traveling wave front that touches the reference point may not be suitable as a reference point for estimating the possibility of collision with actual surrounding objects, except for rear-end collisions with a following vehicle / road user, etc. Therefore, for example, if the exit reference point must be used as a reference point for positioning a V2X message, it may be necessary to correct the actual reference point by taking into account the length of the vehicle, etc. For example, after the vehicle has completely entered, or if the specifications of the vehicle, etc. are known through the image detection results or related messages, etc., correction may be possible by referring to information about the specifications of the vehicle, etc. However, for example, if this is also impossible, the reference point may not be transmitted, or the length of the object may be estimated / corrected and transmitted by taking into account the type of the detected object (e.g., a sedan-type passenger car, approximately 5 m in length), or the exit reference point may be transmitted as a reference point for positioning, but the accuracy of the position error may be set to be very low and transmitted.

[0128] According to one embodiment of the present disclosure, when a reference point is set (e.g., as described above) and location information of the reference point is transmitted using an existing V2X message, in some cases, the information may not be transmitted or inaccurate information may be transmitted. For example, this problem may be solved if additional information related to the reference point is transmitted by attaching it to an existing V2X message such as a BSM (Basic Safety Message) / PSM (Personal Safety Message) or by transmitting it through a new type of message. For example, some or all of the type of reference point, the relative position of the reference point from the corresponding object, and the actually measured / calculated positions of the reference point may be distinguished and transmitted.

[0129] According to one embodiment of the present disclosure, more specifically, it is possible to determine whether the front (or entry reference point) of an object, the rear (exit reference point), or both or neither is detected through a differential image. In particular, in cases where both the entry reference point and the exit reference point are detected, only the entry reference point (i.e., the direction of travel and the reference point are aligned) may be set as a representative value.

[0130] According to one embodiment of the present disclosure, when determining two reference points, a difference image for determining an entry reference point and a difference image for determining an exit reference point may be compared, and the one in which a greater amount of difference (indicating meaningful image information (for determining a reference point)) occurs may be determined as the actual reference point.

[0131] According to one embodiment of the present disclosure, information on the reference point may be set and transmitted in a message transmitting object detection information (e.g., CPM (Collective Perception. Message), SDSM (Sensor Data Sharing Message), …). For example, a field of a message distinguishing a reference point may be expressed as a (1-bit) flag depending on whether it is an entry / exit reference point (e.g., 0 = entry reference point, 1 = entry reference point). Alternatively, a (2-bit) field may be configured in a bitmap format for each entry / exit reference point (e.g., when MSB (most significant bit) = entry reference point, LSB (least significant bit) = exit reference point, 00 = reference point not detected, 10 = entry reference point detected, 01 = exit reference point detected, 11 = both detected).

[0132] According to one embodiment of the present disclosure, if the above-mentioned entry reference point is set to be detected, there may not be a significant problem in performing services such as collision warning even if a value for the size of the object, for example, the length, is not set, and the accuracy and / or reliability values ​​for the location information may be set to be high. For example, if the error value due to the distance from the object in the corresponding image detection area, the resolution of the image, etc. is 10 cm, the accuracy and / or reliability value corresponding to the location information error of 10 cm can be used as is.

[0133] According to one embodiment of the present disclosure, if a value for the size (e.g., length) of an object is not set when the exit reference point is set to be detected, an error may occur in performing services such as collision warning. Therefore, in this case, for example, the accuracy and / or reliability values ​​for the location information (from a service perspective) may be set to be low, and especially when the length of the object is very long, this may have the effect of producing a very large error in the location information. However, for example, if a new reference point is generated with a certain offset (related to the length of the object) from the exit reference point, the error value of the location information can be reduced, and the accuracy or reliability, etc. can be increased.

[0134] According to one embodiment of the present disclosure, the length of the object may be actually measured and reflected in the offset. For example, the length of the object may be determined through an image processing method, and adding half of the length in the direction of travel may become the center point of the object, and / or, adding the length in the direction of travel may become the entry reference point of the object. For example, in this case, the error value, accuracy, or reliability of the location information may be determined depending on the method of measuring / deriving the vehicle length. For example, if a very accurate method is used, the error value of the location information may be reduced and the accuracy or reliability may be increased.

[0135] FIG. 21 illustrates a method for obtaining the length of an object according to an embodiment of the present disclosure. The embodiment of FIG. 21 may be combined with various embodiments of the present disclosure.

[0136] Referring to FIG. 21, according to one embodiment of the present disclosure, as an example of a method of measuring the length of the object, there may be a method of using the difference between the entry reference point and the exit reference point of the object. For example, if the entry reference point and the exit reference point are measured simultaneously at a specific time, the difference in the positions of the two points may be the length of the object. For example, if the entry reference point is detected at a specific time (e.g., t1) and then changed to be detected at another time (e.g., t2) only the exit reference point, the position (P) of the object at t2 during the corresponding period R (t2)) and position at t1 (P F (t1)) may be equal to the object moving more by the length (L) than the difference. For example, the total movement distance of the object may be as in Equation 6. Also, for example, the total movement distance may be expressed as in Equation 7 by adding the product of the object's movement speed (V(t)) in the image and the time it moved at that speed during the period (t1~t2).

[0137]

[0138]

[0139] For example, if it is determined that it moved at a constant speed V(t), it may mean that it moved by V(t)*(t2-t1). For example, if it performed actions such as acceleration and deceleration, it may be necessary to determine the (cumulative) distance considering these actions. At this time, for example, if the object is capable of determining its own location information and / or deriving its velocity and is an object that transmits its location information and / or velocity as a V2X message, the movement distance may be determined by receiving and collating this information during the above period. If a V2X message containing location information and velocity information (V(ki)) is periodically transmitted at a regular interval (e.g. T=100ms), the movement distance may be as shown in Mathematical Expression 8 (wherein k1 = t1, kn = t2 may be mapped or approximated). Therefore, the length of the object can be derived as in Equation 9 and Equation 10 (or, if the transmission cycle can be changed, Ti (where i means the order of discretely transmitting messages) can be substituted instead of T above.)

[0140]

[0141]

[0142]

[0143] FIG. 22 illustrates a method for obtaining the length of an object according to an embodiment of the present disclosure. The embodiment of FIG. 22 may be combined with various embodiments of the present disclosure.

[0144] Referring to FIG. 22, according to one embodiment of the present disclosure, in a situation where the entry reference point and the exit reference point are switched (as described above), if the above method(s) cannot be used, the target object and surrounding objects may all detect reference points in the same direction (e.g., only the entry reference point is detected or only the exit reference point is detected). For example, in this case, the difference in reference points between adjacent objects (e.g., vehicles) may not represent the length of the object in front or behind, but may include the gap between the objects in front and behind. Therefore, for example, when information on reference points of objects (whether entry reference points or exit reference points) is collected or received, the length of the vehicle may be derived by obtaining information on the gap between objects.

[0145] According to one embodiment of the present disclosure, there may be vehicles whose entry reference points are only detected on the video screen, and let's assume that there is a target vehicle A whose length is to be found and a vehicle B behind it. For example, at this time, vehicle B may detect a risk of collision with the vehicle in front (and emergency braking), notify the departure of the vehicle in front, detect motion, or for other purposes such as safe driving, by using an external sensor (e.g., ultrasonic sensor, radar (radio detection and ranging), lidar (light detection and ranging), ...), or an internal sensor (e.g., black box camera, stationary mobile phone camera, ...) of the vehicle B to determine the distance (interval) from the vehicle in front. For example, the entry reference point position (P) of the vehicle A A ) is 110m away and the entry reference point location of vehicle B (P B ) is at the 100m point, the distance measured by vehicle B from vehicle A (D) BA ) is 5.5 m, the length of vehicle A (L A )Is

[0146] L A = P A - P B - DBA = 110 - 100 - 5.5 = 4.5 (m)

[0147] It could be.

[0148] According to one embodiment of the present disclosure, the distance information between vehicles thus determined may be transmitted through V2X messages such as CPM (Collective Perception Message) and SDSM (Sensor Data Sharing Message) that transmit recognized and sensed information, and for example, since maintaining an appropriate distance between vehicles may correspond to basic safety in traffic, it may be transmitted through V2X messages such as BSM (Basic Safety Message) and CAM (Cooperative Awareness Message).

[0149] According to one embodiment of the present disclosure, for example, a perceived object container of a CPM transmitted by a specific vehicle may include distance, speed, reference point information, etc. related to a perceived object in the vicinity. For example, the distance information may be measured based on reference point information that is also included in the container. Therefore, for example, if a distance to a forward vehicle is to be indicated by distinguishing the vehicle in front, a separate explicit indication may be provided. For example, a data field or data element indicating a forward vehicle (or forward object) may exist within the perceived object container, and for example, it may be set / configured to 0 for other objects, and for example, when a forward vehicle is sensed, this field may be set / configured to 1. Alternatively, for example, more implicitly, the closest vehicle among the vehicles driving ahead in the same lane as the specific vehicle may correspond to the preceding vehicle. For example, if the length of the vehicle obtained implicitly in this way is significantly different from the length that the vehicle category can have (e.g., vehicle type = passenger car, length = 40 m), it may be determined that there is an error in the method of deriving the length.

[0150] According to one embodiment of the present disclosure, or when using a rough measurement method, the error value, accuracy, or reliability of the location information may not be very low or very high. For example, a motion vector can be generated from the exit reference point mapped to an image of a specific object acquired through background removal, and for example, the point where a straight line extended in the direction of movement of the motion vector intersects (penetrates) the image of the object can be roughly set as an entry reference point. For example, this may be the same as the actual entry reference point or slightly ahead (based on the direction of movement), and in terms of V2X service, there may not be a major disadvantage other than generating the effect of generating a warning message a little more conservatively.

[0151] According to one embodiment of the present disclosure, if specific specification information about the object can be obtained from a road side unit (RSU) / base station, etc., the entry reference point, center point, etc. can be identified by reflecting the actual length information, and the error, accuracy, reliability, etc. of the entry reference point, center point, etc. may depend on the accuracy of the specification information or the accuracy of identifying the actual manufacturer and model information of the object. For example, even if the specific specification information cannot be obtained, the entry reference point, center point, etc. can be roughly identified by identifying type information (e.g., sedan, SUV, truck, bus, etc.) or detailed category information (e.g., 15-seater bus, 45-seater bus, etc.). For example, or if the object is an object transmitting a V2X message, the reference point can be corrected by identifying manufacturer or model information or size (length) information from the V2X message.

[0152] FIG. 23 illustrates a method for obtaining location information according to an embodiment of the present disclosure. The embodiment of FIG. 23 may be combined with various embodiments of the present disclosure.

[0153] Referring to FIG. 23, according to one embodiment of the present disclosure, heading may refer to the direction of a horizontal velocity vector with respect to north (clockwise) (in a world geodetic system (WGS)-84 coordinate system). For example, the horizontal velocity vector may refer to the projection of a 3D velocity vector (on an ellipsoid in a WGS-8 coordinate system). For example, the horizontal speed may refer to the magnitude of the horizontal velocity vector of a reference position. For example, the vehicle orientation / rotational velocity includes the vehicle rotational speed including the yaw-angle (clockwise rotation with reference to north) / yaw rate, the pitch angle / pitch rate, and the roll angle / roll rate. For example, the reference position may mean, for a forward-moving vehicle, the center point of the front side of the bounding box of the vehicle, the anchor point of the bounding box of the vehicle, or the center point of each side of the bounding box of the vehicle and / or a point spaced apart from the center point by the size of the vehicle length in the opposite direction along the longitudinal axis of the vehicle.

[0154] For example, in order to obtain information about a reference position, information about the bounding box of the moving object may first be required. For example, the bounding box of the moving object can be obtained from a projection (image) of the ground surface. For example, information about the reference position may be inaccurate due to changes in the size and / or position of the bounding box. For example, if an object is not fully revealed on the screen (image), the inaccuracy (error) due to incorrect bounding box setting may further increase. As a result, the derived heading, (horizontal) velocity vector, etc. may be calculated incorrectly, which may cause errors in V2X messages that utilize them (e.g., safety messages (BSM), CAM, CPM, etc.).

[0155] According to one embodiment of the present disclosure, the first device can obtain information about the progress (forward advance, backward entry) (boundary) curve of an object based on an image of the object (entity) (an image of the entire object / part of the object, a projection image, a distorted image obtained in the project direction for a projected image corrected / (rotated) transformed into an actual image, a time-difference image of the object, etc.). For example, the first device can obtain information about a specific point on the progress curve of the object (e.g., a point having the smallest y value (vertical position), a center point corresponding to half the width based on the point where the progress curve starts, a point where the normal component of the motion vector of the object (entity) and the slope of the tangent are the same (one or more poles (maximum points, minimum points) on the boundary of the front / rear part of the object)). For example, the specific point can be set as a reference position of the object (entity). For example, the first device can obtain information about the first pole at t1 on the progress curve of the object, where the normal component of the motion vector of the object (entity) and the slope of the tangent are the same. For example, the first device can obtain information about the second pole at t2 after t1 on the progress curve of the object, where the normal component of the motion vector of the object (entity) and the slope of the tangent are the same. For example, the information about the first pole and / or the second Based on the information about the pole, the first device can obtain at least one of information about the motion vector of the object at t2, information about the heading of the object, and information about the direction angle of the object.

[0156] Therefore, according to one embodiment of the present disclosure, additional computations and resulting positioning delays that arise from deriving a reference position based on, for example, an entity's bounding box can be reduced. For example, positioning errors that arise from deriving a reference position based on an entity's bounding box can be reduced.

[0157] FIG. 24 is a diagram illustrating a method for a first device to perform wireless communication according to an embodiment of the present disclosure. The embodiment of FIG. 24 may be combined with various embodiments of the present disclosure.

[0158] Referring to FIG. 24, according to one embodiment of the present disclosure, in step S2410, for example, the first device may obtain first information related to a velocity vector of an entity and second information related to an image of the entity. In step S2420, for example, the first device may obtain third information related to at least one of one or more local maxima or one or more local minima related to the image of the entity based on the first information and the second information. In step S2430, for example, the first device may obtain fourth information related to a reference position of the entity based on the third information.

[0159] Additionally or alternatively, the second information may include segmentation image information about the entity, which is derived from the difference between a full image including the entity and a still image in which no motion occurs within a time interval among the full image.

[0160] Additionally or alternatively, information about a bounding box regarding the boundary of the entity can be obtained.

[0161] Additionally or alternatively, the second information may include partial segmentation image information about the entity, which is derived from the difference between a partial image within the bounding box of the entire image including the entity and a partial still image in which no motion occurs within a time interval among the partial images.

[0162] Additionally or alternatively, the second information may include first differentiated image information between a first image of the entity at a first time and a second image of the entity at a second time after the first time.

[0163] Additionally or alternatively, based on the first differential image information, information regarding whether the reference position is a first reference position forward of the entity can be obtained.

[0164] Additionally or alternatively, the second information may include second differentiated image information between a first image of the entity at a first time and a third image of the entity at a third time earlier than the first time.

[0165] Additionally or alternatively, based on the second differential image information, information regarding whether the reference position is a second reference position with respect to the backward of the entity can be obtained.

[0166] Additionally or alternatively, real image information about the entity can be obtained based on a difference image and a transformation matrix between a first image about the entity at a first time and a second image about the entity at a second time.

[0167] Additionally or alternatively, the transformation matrix may include a rotation transformation matrix.

[0168] Additionally or alternatively, based on the first information and the real image information, third information regarding at least one of the one or more maxima or one or more minima associated with the image regarding the entity may be obtained.

[0169] Additionally or alternatively, the third information may include information about at least one of the first local maxima at a first time or the first local minima at the first time, and information about at least one of the second local maxima at a second time after the first time or the second local maxima at the second time.

[0170] Additionally or alternatively, the first information may include information about a velocity vector of the entity at the first time.

[0171] Additionally or alternatively, based on the first information and the third information, information about the velocity vector of the entity at the second time can be obtained.

[0172] Additionally or alternatively, the first information may include information about a velocity vector of the entity at the first time.

[0173] Additionally or alternatively, based on the first information, the third information, and the transformation matrix, information about the velocity vector of the entity at the second time can be obtained.

[0174] Additionally or alternatively, based on the fourth information about the reference position, information about the heading of the entity can be obtained.

[0175] Additionally or alternatively, a vehicle-to-everything (V2X) message may be transmitted that includes the fourth information regarding the reference location of the entity.

[0176] Additionally or alternatively, the V2X message may include at least one of a Basic safety message (BSM), a Cooperative awareness message (CAM), or a Decentralized environmental notification message (DENM).

[0177] Additionally or alternatively, the fourth information may include information about a first reference position of the entity at a first time, and information about a second reference position of the entity at a second time after the first time.

[0178] Additionally or alternatively, information about the length of the entity can be obtained based on the displacement of the entity from the first time to the second time, and information about the first reference position and information about the second reference position.

[0179] Additionally or alternatively, information about the displacement of the entity from the first time to the second time may be obtained based on fifth information about the speed of the entity and the time at which the fifth information is transmitted.

[0180] Additionally or alternatively, information about the entity and the distance between the entity and other entities may be obtained.

[0181] Additionally or alternatively, based on the information about the distance and the fourth information about the reference position, information about the length of the entity can be obtained.

[0182] The proposed method can be applied to devices according to various embodiments of the present disclosure. First, the memory (104) of the first device (100) may have instructions recorded thereon that cause the first device (e.g., the processor (102), the transceiver (106)) to perform operations based on being executed by the processor (102). For example, the operations may include: the step of: the first device (e.g., the processor (102), the transceiver (106)) obtaining first information related to a velocity vector of an entity and second information related to an image of the entity; the step of obtaining third information related to at least one of one or more local maximum points or one or more local minimum points related to the image of the entity based on the first information and the second information; and / or a step of obtaining fourth information about a reference position of the entity based on the third information;

[0183] In one embodiment, a first device for performing wireless communication is provided. The first device may include at least one transceiver; at least one processor; and at least one memory executably connected to the at least one processor and storing instructions that cause the first device to perform operations based on execution by the at least one processor. For example, the operations may include at least one of: obtaining first information related to a velocity vector of an entity and second information related to an image of the entity; obtaining third information related to at least one of a local maximum point or a local minimum point related to the image of the entity based on the first information and the second information; and / or obtaining fourth information related to a reference position of the entity based on the third information.

[0184] In one embodiment, a processing device adapted to control a first device is provided. The processing device may include at least one processor; and at least one memory executable to the at least one processor and having instructions recorded thereon, the instructions being executed by the at least one processor to cause the first device to perform operations. For example, the operations may include at least one of: obtaining first information relating to a velocity vector of an entity, and second information relating to an image of the entity; obtaining third information relating to at least one of a local maximum point or a local minimum point relating to the image of the entity, based on the first information and the second information; and / or obtaining fourth information relating to a reference position of the entity, based on the third information.

[0185] In one embodiment, a non-transitory computer-readable storage medium having instructions recorded thereon is proposed. The instructions, when executed, may cause a first device to perform operations. For example, the operations may include at least one of: obtaining first information related to a velocity vector of an entity and second information related to an image of the entity; obtaining third information related to at least one of a local maximum point or a local minimum point related to the image of the entity based on the first information and the second information; and / or obtaining fourth information related to a reference position of the entity based on the third information.

[0186] The various embodiments of the present disclosure may be combined with each other.

[0187] Below, a description is given of devices to which various embodiments of the present disclosure can be applied.

[0188] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0189] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0190] FIG. 25 illustrates a communication system (1) according to one embodiment of the present disclosure. The embodiment of FIG. 25 can be combined with various embodiments of the present disclosure.

[0191] Referring to FIG. 25, a communication system (1) to which various embodiments of the present disclosure are applied includes a wireless device, a base station, and a network. Here, the wireless device refers to a device that performs communication using a wireless access technology (e.g., 5G NR (New RAT), LTE (Long Term Evolution)) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (eXtended Reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI device / server (400). For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc. Here, the vehicle may include an Unmanned Aerial Vehicle (UAV) (e.g., a drone) and / or an Aerial Vehicle (AV) (e.g., an Advanced Air Mobility (AAM)). The XR device may include an Augmented Reality (AR) / Virtual Reality (VR) / Mixed Reality (MR) device, and may be implemented in the form of a Head-Mounted Device (HMD), a Head-Up Display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a robot, etc. The portable device may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), a computer (e.g., a laptop, etc.), etc. The home appliance may include a TV, a refrigerator, a washing machine, etc. The IoT device may include a sensor, a smart meter, etc. For example, a base station and a network may also be implemented as a wireless device, and a specific wireless device (200a) may operate as a base station / network node to other wireless devices.

[0192] Here, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification may include not only LTE, NR, and 6G, but also Narrowband Internet of Things for low-power communication. At this time, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology, and may be implemented with standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification may perform communication based on LTE-M technology. At this time, for example, LTE-M technology may be an example of LPWAN technology, and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology can be implemented by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification can include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) considering low-power communication, and is not limited to the above-described names. For example, ZigBee technology can create personal area networks (PAN) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and can be called by various names.

[0193] Wireless devices (100a to 100f) can be connected to a network (300) via a base station (200). Artificial Intelligence (AI) technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (400) via the network (300). The network (300) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, etc. The wireless devices (100a to 100f) can communicate with each other via the base station (200) / network (300), but can also communicate directly (e.g., sidelink communication) without going through the base station / network. For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (Vehicle to Vehicle) / V2X (Vehicle to Everything) communication). In addition, IoT devices (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0194] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a~100f) / base stations (200), and base stations (200) / base stations (200). Here, wireless communication / connection can be achieved through various wireless access technologies (e.g., 5G NR) such as uplink / downlink communication (150a), sidelink communication (150b) (or, D2D communication), and communication between base stations (150c) (e.g., relay, IAB (Integrated Access Backhaul). Through wireless communication / connection (150a, 150b, 150c), wireless devices and base stations / wireless devices, and base stations and base stations can transmit / receive wireless signals to each other. For example, wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), and resource allocation processes can be performed based on various proposals of the present disclosure.

[0195] FIG. 26 illustrates a wireless device according to an embodiment of the present disclosure. The embodiment of FIG. 26 can be combined with various embodiments of the present disclosure.

[0196] Referring to FIG. 26, the first wireless device (100) and the second wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (100), the second wireless device (200)} can correspond to {the wireless device (100x), the base station (200)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 25.

[0197] A first wireless device (100) includes one or more processors (102) and one or more memories (104), and may further include one or more transceivers (106) and / or one or more antennas (108). The processor (102) controls the memories (104) and / or the transceivers (106), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (102) may process information in the memory (104) to generate first information / signal, and then transmit a wireless signal including the first information / signal via the transceiver (106). Furthermore, the processor (102) may receive a wireless signal including second information / signal via the transceiver (106), and then store information obtained from signal processing of the second information / signal in the memory (104). The memory (104) may be connected to the processor (102) and may store various information related to the operation of the processor (102). For example, the memory (104) may perform some or all of the processes controlled by the processor (102), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. Here, the processor (102) and the memory (104) may be part of a communication modem / circuit / chip designed to implement a wireless communication technology (e.g., LTE, NR). The transceiver (106) may be connected to the processor (102) and may transmit and / or receive wireless signals via one or more antennas (108). The transceiver (106) may include a transmitter and / or a receiver. The transceiver (106) may be used interchangeably with an RF (Radio Frequency) unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0198] A second wireless device (200) includes one or more processors (202), one or more memories (204), and may further include one or more transceivers (206) and / or one or more antennas (208). The processor (202) controls the memories (204) and / or the transceivers (206), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202) may process information in the memory (204) to generate third information / signals, and then transmit a wireless signal including the third information / signals via the transceivers (206). In addition, the processor (202) may receive a wireless signal including fourth information / signals via the transceivers (206), and then store information obtained from signal processing of the fourth information / signals in the memory (204). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may perform some or all of the processes controlled by the processor (202), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via one or more antennas (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0199] Hereinafter, the hardware elements of the wireless device (100, 200) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (102, 202). For example, one or more processors (102, 202) may implement one or more layers (e.g., functional layers such as PHY, MAC, RLC, PDCP, RRC, SDAP). One or more processors (102, 202) may generate one or more Protocol Data Units (PDUs) and / or one or more Service Data Units (SDUs) according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. One or more processors (102, 202) may generate messages, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. One or more processors (102, 202) can generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed herein, and provide the signals to one or more transceivers (106, 206). One or more processors (102, 202) can receive signals (e.g., baseband signals) from one or more transceivers (106, 206) and obtain PDUs, SDUs, messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein.

[0200] One or more processors (102, 202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. One or more processors (102, 202) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), one or more Digital Signal Processing Devices (DSPDs), one or more Programmable Logic Devices (PLDs), or one or more Field Programmable Gate Arrays (FPGAs) may be included in one or more processors (102, 202). The descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software configured to perform one or more processors (102, 202) or stored in one or more memories (104, 204) and driven by one or more processors (102, 202). The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and / or sets of instructions.

[0201] One or more memories (104, 204) may be coupled to one or more processors (102, 202) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. The one or more memories (104, 204) may be configured as ROM, RAM, EPROM, flash memory, hard drives, registers, cache memory, computer-readable storage media, and / or combinations thereof. The one or more memories (104, 204) may be located internally and / or externally to the one or more processors (102, 202). Additionally, the one or more memories (104, 204) may be coupled to the one or more processors (102, 202) via various technologies, such as wired or wireless connections.

[0202] One or more transceivers (106, 206) can transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or flowcharts of this document, to one or more other devices. One or more transceivers (106, 206) can receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts of this document, from one or more other devices. For example, one or more transceivers (106, 206) can be connected to one or more processors (102, 202) and can transmit and receive wireless signals. For example, one or more processors (102, 202) can control one or more transceivers (106, 206) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (102, 202) may control one or more transceivers (106, 206) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (106, 206) may be coupled to one or more antennas (108, 208), and one or more transceivers (106, 206) may be configured to transmit and receive user data, control information, wireless signals / channels, or the like, as referred to in the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein, via one or more antennas (108, 208). In this document, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers (106, 206) can convert received user data, control information, wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using one or more processors (102, 202).One or more transceivers (106, 206) may convert user data, control information, wireless signals / channels, etc. processed by one or more processors (102, 202) from baseband signals to RF band signals. For this purpose, one or more transceivers (106, 206) may include an (analog) oscillator and / or filter.

[0203] FIG. 27 illustrates a signal processing circuit for a transmission signal according to an embodiment of the present disclosure. The embodiment of FIG. 27 can be combined with various embodiments of the present disclosure.

[0204] Referring to FIG. 27, the signal processing circuit (1000) may include a scrambler (1010), a modulator (1020), a layer mapper (1030), a precoder (1040), a resource mapper (1050), and a signal generator (1060). Although not limited thereto, the operations / functions of FIG. 27 may be performed in the processor (102, 202) and / or the transceiver (106, 206) of FIG. 26. The hardware elements of FIG. 27 may be implemented in the processor (102, 202) and / or the transceiver (106, 206) of FIG. 26. For example, blocks 1010 to 1060 may be implemented in the processor (102, 202) of FIG. 26. Additionally, blocks 1010 to 1050 may be implemented in the processor (102, 202) of FIG. 26, and block 1060 may be implemented in the transceiver (106, 206) of FIG. 26.

[0205] The codeword can be converted into a wireless signal through the signal processing circuit (1000) of FIG. 27. Here, the codeword is an encoded bit sequence of an information block. The information block can include a transport block (e.g., an UL-SCH transport block, a DL-SCH transport block). The wireless signal can be transmitted through various physical channels (e.g., a PUSCH or a PDSCH).

[0206] Specifically, the codeword can be converted into a bit sequence scrambled by a scrambler (1010). The scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc. The scrambled bit sequence can be modulated into a modulation symbol sequence by a modulator (1020). The modulation method may include pi / 2-BPSK (pi / 2-Binary Phase Shift Keying), m-PSK (m-Phase Shift Keying), m-QAM (m-Quadrature Amplitude Modulation), etc. The complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (1030). The modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (1040) (precoding). The output z of the precoder (1040) can be obtained by multiplying the output y of the layer mapper (1030) by a precoding matrix W of N*M. Here, N is the number of antenna ports, and M is the number of transmission layers. Here, the precoder (1040) can perform precoding after performing transform precoding (e.g., DFT transform) on complex modulation symbols. In addition, the precoder (1040) can perform precoding without performing transform precoding.

[0207] The resource mapper (1050) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources can include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. The signal generator (1060) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna. To this end, the signal generator (1060) can include an Inverse Fast Fourier Transform (IFFT) module, a Cyclic Prefix (CP) inserter, a Digital-to-Analog Converter (DAC), a frequency uplink converter, etc.

[0208] The signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (1010 to 1060) of FIG. 27. For example, a wireless device (e.g., 100, 200 of FIG. 26) can receive wireless signals from the outside through an antenna port / transceiver. The received wireless signals can be converted into baseband signals through a signal restorer. For this purpose, the signal restorer can include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Thereafter, the baseband signal can be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codewords can be restored to the original information blocks through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0209] Figure 28 illustrates a wireless device according to an embodiment of the present disclosure. The wireless device may be implemented in various forms depending on the use case / service (see Figure 25). The embodiment of Figure 28 may be combined with various embodiments of the present disclosure.

[0210] Referring to FIG. 28, the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 26 and may be composed of various elements, components, units / units, and / or modules. For example, the wireless device (100, 200) may include a communication unit (110), a control unit (120), a memory unit (130), and additional elements (140). The communication unit may include a communication circuit (112) and a transceiver(s) (114). For example, the communication circuit (112) may include one or more processors (102, 202) and / or one or more memories (104, 204) of FIG. 26. For example, the transceiver(s) (114) may include one or more transceivers (106, 206) and / or one or more antennas (108, 208) of FIG. 26. The control unit (120) is electrically connected to the communication unit (110), the memory unit (130), and the additional elements (140) and controls the overall operation of the wireless device. For example, the control unit (120) may control the electrical / mechanical operation of the wireless device based on the program / code / command / information stored in the memory unit (130). In addition, the control unit (120) may transmit information stored in the memory unit (130) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (110), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (130).

[0211] The additional element (140) may be configured in various ways depending on the type of the wireless device. For example, the additional element (140) may include at least one of a power unit / battery, an input / output unit (I / O unit), a driving unit, and a computing unit. Although not limited thereto, the wireless device may be implemented in the form of a robot (Fig. 25, 100a), a vehicle (Fig. 25, 100b-1, 100b-2), an XR device (Fig. 25, 100c), a portable device (Fig. 25, 100d), a home appliance (Fig. 25, 100e), an IoT device (Fig. 25, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, an AI server / device (Fig. 25, 400), a base station (Fig. 25, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0212] In FIG. 28, various elements, components, units / parts, and / or modules within the wireless device (100, 200) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (110). For example, within the wireless device (100, 200), the control unit (120) and the communication unit (110) may be wired, and the control unit (120) and the first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (110). In addition, each element, component, unit / part, and / or module within the wireless device (100, 200) may further include one or more elements. For example, the control unit (120) may be configured as one or more processor sets. For example, the control unit (120) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be composed of a random access memory (RAM), a dynamic RAM (DRAM), a read only memory (ROM), a flash memory, a volatile memory, a non-volatile memory, and / or a combination thereof.

[0213] Below, the implementation example of Fig. 28 is described in more detail with reference to the drawings.

[0214] FIG. 29 illustrates a mobile device according to an embodiment of the present disclosure. The mobile device may include a smartphone, a smart pad, a wearable device (e.g., a smartwatch, smartglasses), or a portable computer (e.g., a laptop, etc.). The mobile device may be referred to as a Mobile Station (MS), a User Terminal (UT), a Mobile Subscriber Station (MSS), a Subscriber Station (SS), an Advanced Mobile Station (AMS), or a Wireless Terminal (WT). The embodiment of FIG. 29 may be combined with various embodiments of the present disclosure.

[0215] Referring to FIG. 29, the portable device (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a memory unit (130), a power supply unit (140a), an interface unit (140b), and an input / output unit (140c). The antenna unit (108) may be configured as a part of the communication unit (110). Blocks 110 to 130 / 140a to 140c correspond to blocks 110 to 130 / 140 of FIG. 28, respectively.

[0216] The communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (120) can control components of the mobile device (100) to perform various operations. The control unit (120) can include an AP (Application Processor). The memory unit (130) can store data / parameters / programs / codes / commands required for operating the mobile device (100). In addition, the memory unit (130) can store input / output data / information, etc. The power supply unit (140a) supplies power to the mobile device (100) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (140b) can support connection between the mobile device (100) and other external devices. The interface unit (140b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (140c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (140c) may include a camera, a microphone, a user input unit, a display unit (140d), a speaker, and / or a haptic module.

[0217] For example, in the case of data communication, the input / output unit (140c) obtains information / signals (e.g., touch, text, voice, image, video) input by the user, and the obtained information / signals can be stored in the memory unit (130). The communication unit (110) converts the information / signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station. In addition, the communication unit (110) can receive wireless signals from other wireless devices or base stations, and then restore the received wireless signals to the original information / signals. The restored information / signals can be stored in the memory unit (130) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (140c).

[0218] FIG. 30 illustrates a vehicle or autonomous vehicle according to one embodiment of the present disclosure. The vehicle or autonomous vehicle may be implemented as a mobile robot, a car, a train, a manned or unmanned aerial vehicle (AV), a ship, or the like. The embodiment of FIG. 30 may be combined with various embodiments of the present disclosure.

[0219] Referring to FIG. 30, a vehicle or autonomous vehicle (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a driving unit (140a), a power supply unit (140b), a sensor unit (140c), and an autonomous driving unit (140d). The antenna unit (108) may be configured as a part of the communication unit (110). Blocks 110 / 130 / 140a to 140d correspond to blocks 110 / 130 / 140 of FIG. 28, respectively.

[0220] The communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, road side units, etc.), and servers. The control unit (120) can control elements of the vehicle or autonomous vehicle (100) to perform various operations. The control unit (120) can include an ECU (Electronic Control Unit). The drive unit (140a) can drive the vehicle or autonomous vehicle (100) on the ground. The drive unit (140a) can include an engine, a motor, a power train, wheels, brakes, a steering device, etc. The power supply unit (140b) supplies power to the vehicle or autonomous vehicle (100) and can include a wired / wireless charging circuit, a battery, etc. The sensor unit (140c) can obtain vehicle status, surrounding environment information, user information, etc. The sensor unit (140c) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an incline sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc. The autonomous driving unit (140d) may implement a technology for maintaining a driving lane, a technology for automatically controlling speed such as adaptive cruise control, a technology for automatically driving along a set path, a technology for automatically setting a path and driving when a destination is set, etc.

[0221] For example, the communication unit (110) can receive map data, traffic information data, etc. from an external server. The autonomous driving unit (140d) can generate an autonomous driving route and driving plan based on the acquired data. The control unit (120) can control the drive unit (140a) so that the vehicle or autonomous vehicle (100) moves along the autonomous driving route according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (110) can irregularly / periodically acquire the latest traffic information data from an external server and can acquire surrounding traffic information data from surrounding vehicles. In addition, during autonomous driving, the sensor unit (140c) can acquire vehicle status and surrounding environment information. The autonomous driving unit (140d) can update the autonomous driving route and driving plan based on newly acquired data / information. The communication unit (110) can transmit information regarding the vehicle location, autonomous driving route, driving plan, etc. to the external server. External servers can predict traffic information data in advance using AI technology or other technologies based on information collected from vehicles or autonomous vehicles, and provide the predicted traffic information data to the vehicles or autonomous vehicles.

[0222] The claims set forth in this specification may be combined in various ways. For example, the technical features of the method claims of this specification may be combined and implemented as a device, and the technical features of the device claims of this specification may be combined and implemented as a method. Furthermore, the technical features of the method claims and the technical features of the device claims of this specification may be combined and implemented as a device, and the technical features of the method claims and the technical features of the device claims of this specification may be combined and implemented as a method.

Claims

1. In a method for performing wireless communication by a first device, A step of obtaining first information related to a velocity vector of an entity and second information related to an image of the entity; A step of obtaining third information about at least one of one or more local maximum points or one or more local minimum points related to the image of the entity based on the first information and the second information; and A method comprising: a step of obtaining fourth information about a reference position of the entity based on the third information; 2. In paragraph 1, A method wherein the second information includes segmentation image information regarding the entity, which is derived through the difference between a full image including the entity and a still image in which no motion occurs within a time interval among the full image.

3. In paragraph 1, Further comprising a step of obtaining information about a bounding box regarding the boundary of the above entity; A method wherein the second information includes partial segmentation image information regarding the entity, which is derived through the difference between a partial image within the bounding box among the entire image including the entity and a partial still image in which no motion occurs within a time interval among the partial images.

4. In paragraph 1, The second information includes first differential image information between a first image of the entity at a first time and a second image of the entity at a second time after the first time, and A method further comprising: a step of obtaining information on whether the reference position is a first reference position with respect to the forward of the entity based on the first differential image information; 5. In paragraph 1, The second information includes second differential image information between a first image of the entity at a first time and a third image of the entity at a third time earlier than the first time, and A method further comprising: a step of obtaining information on whether the reference position is a second reference position relative to the backward of the entity based on the second differential image information; 6. In paragraph 1, A method further comprising: obtaining real image information about the entity based on a difference image and a transformation matrix between a first image about the entity at a first time and a second image about the entity at a second time.

7. In paragraph 6, A method wherein the above transformation matrix includes a rotation transformation matrix.

8. In paragraph 6, A method in which third information is obtained about at least one of the one or more maxima or one or more minima related to the image of the entity based on the first information and the real image information.

9. In paragraph 1, A method wherein the third information comprises information about at least one of the first local maxima at a first time or the first local minima at the first time, and information about at least one of the second local maxima at a second time after the first time or the second local maxima at the second time.

10. In paragraph 9, The first information includes information about the velocity vector of the entity at the first time, A method further comprising: a step of obtaining information about a velocity vector of the entity at the second time based on the first information and the third information.

11. In paragraph 10, The first information includes information about the velocity vector of the entity at the first time, A method further comprising: a step of obtaining information about a velocity vector of the entity at the second time based on the first information, the third information, and a transformation matrix.

12. In paragraph 1, A method further comprising: a step of obtaining information about a heading of the entity based on the fourth information about the reference position; 13. In paragraph 1, A method further comprising: transmitting a V2X (vehicle-to-everything) message including the fourth information regarding the reference location of the entity.

14. In paragraph 13, A method wherein the V2X message includes at least one of a BSM (Basic safety message), a CAM (Cooperative awareness message), or a DENM (Decentralized environmental notification message).

15. In paragraph 1, The fourth information includes information about a first reference position of the entity at a first time, and information about a second reference position of the entity at a second time after the first time, A method further comprising: obtaining information about a length of the entity based on a displacement of the entity from the first time to the second time, and information about the first reference position and information about the second reference position.

16. In paragraph 15, A method wherein information about the displacement of the entity from the first time to the second time is obtained based on fifth information about the speed of the entity and the time at which the fifth information is transmitted.

17. In paragraph 1, Further comprising a step of obtaining information about the distance between the entity and a different entity; A method further comprising: a step of obtaining information about the length of the entity based on the information about the distance and the fourth information about the reference position.

18. In a first device performing wireless communication, At least one transmitter / receiver; at least one processor; and At least one memory executable connected to said at least one processor and having instructions recorded thereon that cause said first device to perform operations based on being executed by said at least one processor, said operations comprising: A step of obtaining first information related to a velocity vector of an entity and second information related to an image of the entity; A step of obtaining third information about at least one of one or more local maximum points or one or more local minimum points related to the image of the entity based on the first information and the second information; and A first device comprising: a step of obtaining fourth information about a reference position of the entity based on the third information; 19. In a processing device adapted to control a first device, The above processing device, at least one processor; and At least one memory executable to said at least one processor, and having instructions recorded thereon that cause said first device to perform operations based on being executed by said at least one processor, said operations comprising: A step of obtaining first information related to a velocity vector of an entity and second information related to an image of the entity; A step of obtaining third information about at least one of one or more local maximum points or one or more local minimum points related to the image of the entity based on the first information and the second information; and A processing device comprising: a step of obtaining fourth information about a reference position of the entity based on the third information; 20. A non-transitory computer-readable storage medium that records commands, The above instructions, when executed, cause the first device to perform actions, wherein the actions are: A step of obtaining first information related to a velocity vector of an entity and second information related to an image of the entity; A step of obtaining third information about at least one of one or more local maximum points or one or more local minimum points related to the image of the entity based on the first information and the second information; and A non-transitory computer-readable storage medium, comprising: a step of obtaining fourth information about a reference position of the entity based on the third information;

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