Sensing method and apparatus

Abstract

A sensing method and apparatus. A fusion center receives at least one piece of sensing data from at least one sensing node, wherein first sensing data among the at least one piece of sensing data is from a first sensing node, second sensing data among the at least one piece of sensing data is from a second sensing node, both the first sensing data and the second sensing data include sensing data of a first area, and the sensing data of the first area included in each of the first sensing data and the second sensing data corresponds to at least two data types. The fusion center determines a sensing result on the basis of the at least one piece of sensing data. The fusion center can determine the sensing result on the basis of sensing data of more data types, thereby improving sensing accuracy, and reducing a missed detection rate. The first sensing node can correct the value of a first parameter on the basis of the deviation of a first sensing result, thereby improving the accuracy of the first parameter. The fusion center performs point cloud fusion on the basis of the corrected value of the first parameter, thereby being conducive to improving sensing accuracy.

Description

A sensing method and device

[0001] Cross-reference to related applications

[0002] This application claims priority to Chinese Patent Application No. 202510485551.X, filed on April 16, 2025, entitled "A Sensing Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of sensing technology, and in particular to a sensing method and apparatus. Background Technology

[0004] Sensing refers to the detection of parameters of targets in the physical environment, such as their position and velocity. It can also be called detection. The processing flow of sensing signals involves the processing of sensing nodes and sensing network elements. For example, sensing nodes are responsible for sending and / or receiving sensing signals, as well as related baseband processing, ultimately outputting the sensing results to the sensing network elements. The sensing network elements are responsible for processing the sensing results reported by the sensing nodes, such as identifying the sensed targets.

[0005] How to improve the accuracy of perception is a problem that needs to be solved. Summary of the Invention

[0006] This application provides a sensing method and apparatus to improve sensing accuracy.

[0007] Firstly, a first sensing method is provided, which can be applied to a first device. The first device is, for example, a fusion center, a functional module included in a fusion center, or a larger device including a fusion center. The first device is, for example, a network-side device. This network-side device is also referred to as a network device. The network device is, for example, a network equipment, or other equipment including network equipment functions, or a circuit, or a chip system (or chip) or other functional module capable of implementing the functions of the network equipment, and is, for example, disposed within the network equipment. The network equipment includes, for example, core network equipment and / or access network equipment, or includes equipment located between the core network and the access network. The access network equipment can be a non-ORAN architecture or an ORAN architecture; or, the access network equipment can be a CU, DU, or RU under an ORAN architecture. The access network equipment is, for example, located on the ground, or the access network equipment is, for example, a satellite, or located on a satellite. The core network equipment is, for example, a network element capable of implementing sensing functions such as SF or LMF. The method includes: receiving at least one sensing result, the at least one sensing result coming from at least one sensing node, a first sensing result in the at least one sensing result including a first value, the first value being a value of a first parameter; sending first information, the first information being used to determine a deviation of the first sensing result, the first information being determined based on the at least one sensing result; and receiving a second value, the second value being determined based on the first information and the first value.

[0008] In this embodiment, the first sensing node can determine the deviation of the first sensing result based on the first information, and then correct the value of the first parameter based on the deviation, thereby improving the accuracy of the first parameter. The fusion center performs point cloud fusion based on the corrected value of the first parameter, which helps to improve the sensing accuracy.

[0009] In one optional implementation, the first perception result and the second value correspond to the same perception target. The second value and the first perception result correspond to the same perception target, and the second value can be regarded as a correction to the value of the first parameter included in the first perception result, thereby making the perception result of the fusion center for the perception target more accurate.

[0010] In one optional implementation, the at least one sensing result is point cloud information. For example, the at least one sensing result is at least one point cloud information.

[0011] In one optional implementation, sending the first information includes sending the first information to a first sensing node. The first information indicates a deviation in the first sensing result, therefore the first information can be sent to the first sensing node. Optionally, at least one sensing result other than the first sensing result may also have deviations, in which case the fusion center may also send corresponding information to the sensing nodes corresponding to the other sensing results to indicate the deviations. The deviations of different sensing results may be the same or different.

[0012] In one alternative implementation, the first parameter includes one or more of the following: error covariance parameter, signal-to-noise ratio, error elliptic parameter, error variance parameter, or received signal strength.

[0013] In one optional implementation, the deviation of the first perception result is the deviation between the position of the perceived target corresponding to the first perception result and the reference position. The deviation of the first perception result can refer to a positional deviation. The position of the perceived target corresponding to the first perception result is, for example, the position of the target point corresponding to the first perception result. This target point is, for example, the target point corresponding to the perceived target. It can be understood that the first perception node can obtain the first perception result based on the perception or detection of the perceived target, and the first perception result may not be the complete perceived target, but rather the target point of the perceived target. Therefore, the position of the perceived target corresponding to the first perception result is considered to be the position of the target point. If the position of the target point is different from the reference position, it indicates that the first perception result has a deviation, and therefore, the first information can indicate this deviation.

[0014] In one optional implementation, the reference position is determined based on the contour of the perceived target, which corresponds to the first perception result and the second value. The reference position can be determined based on the contour of the perceived target, or it can be determined in other ways, allowing for flexibility in its selection.

[0015] In one alternative implementation, the reference location is the geometric center or centroid of the sensing target. Alternatively, the reference location can be any other point on the sensing target; there is no limitation on this.

[0016] In an optional implementation, the method further includes: determining the contour of the perceived target based on the at least one perception result. The fusion center receives at least one perception result and can determine the contour of the perceived target accordingly, thereby determining the deviation of the first perceived target. Here, the perceived target may refer to the perceived target corresponding to the first perception result; for at least one perception result, the corresponding perceived targets may be the same or different. If there are other perception results among the at least one perception result corresponding to other perceived targets, optionally, the fusion center can also determine the contour of the other perceived targets based on the at least one perception result; the methods are similar and will not be elaborated further.

[0017] In one optional implementation, determining the contour of the perceived target based on the at least one perception result includes: clustering the target points indicated by the at least one perception result, and determining the contour based on the clustering results; or, inputting the at least one perception result into a first AI model to obtain information about the contour output by the first AI model. The fusion center can determine the contour through clustering or through the first AI model, offering greater flexibility.

[0018] In one optional implementation, the first information is used to indicate the deviation; or, the first information is used to indicate the contour of the perceived target, the perceived target being the perceived target corresponding to the first perception result and the second value; or, the first information is used to indicate the size of the perceived target and the direction of movement of the perceived target, the perceived target being the perceived target corresponding to the first perception result and the second value. The first information can directly indicate the deviation, and the sensing node can determine the deviation based on the first information without performing any further processing. Alternatively, the first information can indicate the contour, or indicate the size and direction of movement, etc., which can reduce the process of the fusion center determining the deviation and simplify the implementation of the fusion center.

[0019] In one alternative implementation, the size of the perceived target is determined based on its outline or is a preset size. The fusion center can determine this size based on the outline of the perceived target; or the size can be preset, for example, the size of a specific vehicle model can be a specified size, thereby simplifying the implementation of the fusion center.

[0020] In an optional implementation, the method further includes: sending second information to a second sensing node, the second information being used to determine a deviation in a second sensing result, the second sensing result being included in the at least one sensing result. The at least one sensing result may, for example, also include a second sensing result from the second sensing node. The fusion center may also determine the second information in a manner similar to that used to determine the first information, in which case the fusion center can send the second information to the second sensing node, enabling the second sensing node to also correct the second sensing result.

[0021] In one optional implementation, the deviation of the second perception result is the deviation between the position of the perceived target corresponding to the second perception result and the reference position.

[0022] In an optional implementation, the method further includes performing point cloud fusion based on the second value. For example, the fusion center can perform point cloud fusion based on the second value of the first parameter and other information included in the first perception result besides the first parameter. Optionally, when performing point cloud fusion, the fusion center can also combine at least one perception result other than the first perception result that corresponds to the perception target (i.e., the perception target corresponding to the first perception result), without limitation.

[0023] Secondly, a second sensing method is provided, which can be applied to a second device. The second device is, for example, a first sensing node, a functional module included in the first sensing node, or a larger device including the first sensing node. The second device is, for example, a network-side device or a terminal-side device. The network-side device is also referred to as a network device. The network device is, for example, a network equipment, or other equipment including network equipment functions, or a circuit, or a chip system (or chip) or other functional module capable of implementing the functions of the network equipment, and the chip system or functional module is, for example, disposed within the network equipment. The network equipment includes, for example, an access network device; a description of access network devices can be found in the first aspect. The terminal-side device is also referred to as a terminal device. The terminal device is, for example, a terminal equipment, or other equipment including terminal equipment functions, or a circuit, or a system-on-a-chip (or a chip, such as a modem chip, also known as a baseband chip, or a system-on-a-chip (SoC) chip or system-in-a-package (SIP) chip containing a modem core) or other functional module, which can realize the functions of the terminal equipment, and which is, for example, disposed in the terminal equipment. The method includes: sending a first sensing result, the first sensing result including a first value, the first value being the value of a first parameter; receiving first information, the first information used to determine a deviation of the first sensing result; and sending a second value, the second value being determined based on the first information and the first value.

[0024] In one alternative implementation, the first perception result and the second value correspond to the same perception target.

[0025] In one alternative implementation, the first perception result is point cloud information.

[0026] In one optional implementation, the first information is determined based on at least one perception result, the at least one perception result including the first perception result and a second perception result, the second perception result coming from a second perception node, and the first perception result and the second perception result corresponding to the same perception target.

[0027] In one alternative implementation, the first parameter includes one or more of the following: error covariance parameter, signal-to-noise ratio, error elliptic parameter, error variance parameter, or received signal strength.

[0028] In one optional implementation, the deviation of the first perception result is the deviation between the position of the perceived target corresponding to the first perception result and the reference position.

[0029] In one alternative implementation, the first information is used to indicate the deviation; or, the first information is used to indicate the outline of the sensing target; or, the first information is used to indicate the size of the sensing target and the direction of movement of the sensing target.

[0030] In one optional implementation, the first parameter includes an error covariance parameter, and the method further includes: determining a second distance based on the deviation and a first distance, and determining a second angle based on the deviation and a first angle, wherein the first distance is the distance between the detected sensing target and the first sensing node, and the first angle is the angle between the detected sensing target and the first sensing node; and determining a second value based on the second distance and the second angle.

[0031] For information on the technical effects of the second aspect or some of the optional implementation methods, please refer to the description of the technical effects of the first aspect or corresponding implementation methods.

[0032] Thirdly, an apparatus is provided. The apparatus can be the first apparatus described in the first aspect above. The apparatus possesses the functions of the first apparatus described above. For example, the apparatus is capable of implementing the functions described in the first aspect above. For instance, the apparatus includes modules, units, or means corresponding to performing the operations involved in the first aspect above. These modules, units, or means can be implemented through software, hardware, or a combination of software and hardware. The first apparatus is, for example, a network device, or other device including network device functions, or a chip system (or chip or circuit) or other functional module capable of implementing the functions of a network device. This chip system or functional module is, for example, disposed within a network device. The network device includes, for example, core network equipment and / or access network equipment, or equipment located between the core network and the access network. In one optional implementation, the apparatus includes a baseband device and a radio frequency device. In another optional implementation, the apparatus includes a processing unit (sometimes also called a processing module) and a transceiver unit (sometimes also called a transceiver module). A transceiver unit can perform both sending and receiving functions. When the transceiver unit performs the sending function, it can be called a sending unit (sometimes also called a sending module), and when it performs the receiving function, it can be called a receiving unit (sometimes also called a receiving module). The sending unit and the receiving unit can be the same functional module, which is called the transceiver unit and can perform both sending and receiving functions; or, the sending unit and the receiving unit can be different functional modules, and the transceiver unit is a collective term for these functional modules.

[0033] In one optional implementation, the transceiver unit (or the receiving unit) is configured to receive at least one sensing result, the at least one sensing result coming from at least one sensing node, wherein a first sensing result among the at least one sensing result includes a first value, the first value being the value of a first parameter; the transceiver unit (or the sending unit) is configured to send first information, the first information being used to determine a deviation of the first sensing result, the first information being determined based on the at least one sensing result; the transceiver unit (or the receiving unit) is further configured to receive a second value, the second value being determined based on the first information and the first value.

[0034] In an alternative embodiment, the device further includes a storage unit (sometimes also called a storage module), the processing unit being coupled to the storage unit and executing programs or instructions in the storage unit to enable the device to perform the functions of the first device described in the first aspect above.

[0035] Fourthly, an apparatus is provided. The apparatus can be the second apparatus described in the second aspect above. The apparatus possesses the functions of the second apparatus described above. For example, the apparatus is capable of implementing the functions described in the second aspect above. For instance, the apparatus includes modules, units, or means corresponding to performing the operations involved in the second aspect above. These modules, units, or means can be implemented through software, hardware, or a combination of software and hardware. The second apparatus is, for example, a terminal device, or other device including terminal device functions, or a chip system (or chip or circuit) or other functional module capable of implementing the functions of a terminal device, and is, for example, disposed in a terminal device. Alternatively, the second apparatus is, for example, a network device, or other device including network device functions, or a chip system (or chip or circuit) or other functional module capable of implementing the functions of a network device, and is, for example, disposed in a network device. The network device includes, for example, an access network device. In an optional implementation, the apparatus includes a baseband device and a radio frequency device. In another alternative implementation, the apparatus includes a processing unit (sometimes also called a processing module) and a transceiver unit (sometimes also called a transceiver module). For details on the implementation of the transceiver unit, please refer to the relevant description in the third aspect.

[0036] In one optional implementation, the transceiver unit (or the sending unit) is configured to send a first sensing result, the first sensing result including a first value, the first value being the value of a first parameter; the transceiver unit (or the receiving unit) is configured to...

[0037] The transceiver unit (or the sending unit) receives first information, which is used to determine the deviation of the first sensing result; the transceiver unit is further used to send a second value, which is determined based on the first information and the first value.

[0038] In an alternative embodiment, the device further includes a storage unit (sometimes also called a storage module), the processing unit being coupled to the storage unit and executing programs or instructions in the storage unit to enable the device to perform the functions of the second device described in the second aspect above.

[0039] Fifthly, an apparatus is provided, the apparatus comprising a memory and one or more processors. The memory is used to store part or all of a computer program or instructions necessary for implementing the functions involved in the first or second aspect described above. The one or more processors are executable to carry out the computer program or instructions, such that, when executed, the apparatus implements the methods in any possible design or implementation of the first or second aspect described above.

[0040] In one possible design, the device may further include interface circuitry, wherein the processor is configured to communicate with other devices or components via the interface circuitry.

[0041] In one possible design, the device may also include the memory.

[0042] The aforementioned device may be a network device, a communication module in a network device, or a chip in a network device that is responsible for communication functions, such as a modem chip (also known as a baseband chip) or a SoC or SIP chip that contains a modem module.

[0043] A sixth aspect provides an apparatus comprising a memory and one or more processors. The memory is used to store part or all of a computer program or instructions necessary for implementing the functions described in the second aspect above. The one or more processors are executable to carry out the computer program or instructions, such that, when executed, the apparatus implements the methods in any possible design or implementation of the second aspect above.

[0044] In one possible design, the device may further include interface circuitry, wherein the processor is configured to communicate with other devices or components via the interface circuitry.

[0045] In one possible design, the device may also include the memory.

[0046] The aforementioned device may be a terminal device, a communication module in a terminal device, or a chip in a terminal device that is responsible for communication functions, such as a modem chip (also known as a baseband chip) or a SoC or SIP chip that contains a modem module.

[0047] A seventh aspect provides a sensing system including a fusion center. The fusion center is used to perform the method described in the first aspect, which is executed by the first device. For example, the fusion center can be implemented using the device described in the third or fifth aspect.

[0048] Optionally, the sensing system may further include at least one sensing node, for example, any one of the at least one sensing node being a first sensing node. The first sensing node is used to perform the method executed by the second apparatus as described in the second aspect above. The first sensing node is, for example, a terminal device or a network device (e.g., an access network device). For example, the terminal device can be implemented using the apparatus described in the fourth or sixth aspect; the network device can be implemented using the apparatus described in the fourth or fifth aspect.

[0049] Eighthly, a computer-readable storage medium is provided for storing a computer program or instructions that, when executed, cause the method performed by the first or second means in the preceding aspects to be implemented.

[0050] Ninthly, a computer program product containing instructions is provided, which, when the computer program or instructions are run on a computer, causes the methods described in the above aspects to be implemented.

[0051] In a tenth aspect, a chip system is provided, including a processor and an interface, the processor being configured to call and execute instructions from the interface to enable the chip system to implement the methods described above. Attached Figure Description

[0052] Figure 1 is a schematic diagram of a single-station sensing mode;

[0053] Figure 2 is a schematic diagram of the dual-station sensing mode;

[0054] Figures 3 and 4 show examples of two point cloud fusion results for the fusion center;

[0055] Figures 5 and 6 are schematic diagrams of two application scenarios of the embodiments of this application;

[0056] Figure 7 is a flowchart of a sensing method provided in an embodiment of this application;

[0057] Figure 8 is an example of a clustering method in an embodiment of this application;

[0058] Figure 9 is an example of the error variance parameter in an embodiment of this application;

[0059] Figure 10 is a schematic diagram of a device provided in an embodiment of this application;

[0060] Figure 11 is a schematic diagram of another device provided in an embodiment of this application. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0062] In this application embodiment, the number of nouns, unless otherwise specified, refers to "singular nouns or plural nouns," that is, "one or more." "At least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, or B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the related objects before and after are in an "or" relationship. For example, A / B means: A or B. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c means: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0063] The ordinal numbers such as "first" and "second" mentioned in the embodiments of this application are used to distinguish multiple objects, and are not used to limit the size, content, order, timing, priority, or importance of the multiple objects. Furthermore, the numbering of steps in the various embodiments described in this application is only to distinguish different steps and is not used to limit the order in which the steps are performed.

[0064] The following explanations of some terms or concepts used in the embodiments of this application are provided to facilitate understanding by those skilled in the art.

[0065] In this embodiment, the terminal device is a device with wireless transceiver capabilities, which can be a fixed device, a mobile device, a handheld device (e.g., a mobile phone), a wearable device, an in-vehicle device, or a wireless device (e.g., a communication module, a modem, or a chip system, etc.) built into the aforementioned devices. The terminal device is used to connect people, objects, machines, etc., and can be widely used in various scenarios, including but not limited to the following: sensing scenarios, cellular communication, device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine / machine-type communications (M2M / MTC) communication, Internet of Things (IoT), virtual reality (VR), augmented reality (AR), industrial control, self-driving, remote medical care, smart grid, smart furniture, smart office, smart wearables, smart transportation, smart city, drones, robots, and indoor commercial scenarios (such as mobile phone screen mirroring, file sharing, and mobile phone to VR glasses video transmission). When the terminal equipment is applied to V2X, it can also be called a V2X device, such as a smart car, digital car, unmanned car, driverless car, pilotless car, or automobile, self-driving car, or autonomous car, pure electric vehicle (EV), hybrid electric vehicle (HEV), range-extended electric vehicle (REEV), plug-in hybrid electric vehicle (PHEV), new energy vehicle, or roadside unit (RSU). The terminal equipment can also be a device used in D2D communication, such as an electricity meter or water meter.

[0066] Furthermore, in this embodiment, the terminal device can also be a terminal device in an IoT system. IoT is an important component of the future development of information technology. Its main technical feature is to connect objects to the network through communication technology, thereby realizing an intelligent network of human-machine interconnection and object-to-object interconnection.

[0067] The various terminal devices described above, if located in a vehicle (e.g., placed inside or installed inside a vehicle), can all be considered in-vehicle terminal devices, also known as on-board units (OBUs). The terminal device of this application can also be an in-vehicle module, in-vehicle component, in-vehicle chip, or in-vehicle unit built into a vehicle as one or more components or units. The vehicle can implement the methods of this application through the built-in in-vehicle module, in-vehicle component, in-vehicle chip, or in-vehicle unit.

[0068] The terminal equipment may sometimes be referred to as user equipment (UE), terminal, access station, UE station, remote station, wireless communication equipment, or user device, etc.

[0069] In this application embodiment, the communication device used to implement the terminal device function can be the terminal device itself, or it can be a device capable of supporting the terminal device in implementing the function, such as a chip system. This device can be installed in the terminal device. In the technical solutions provided in this application embodiment, the terminal device is used as an example to describe the technical solutions provided in this application embodiment. Furthermore, for ease of description, the terminal device in this application embodiment is described using a UE as an example.

[0070] The network devices in this application embodiment include, for example, access network devices and / or core network devices. The access network devices are devices with wireless transceiver capabilities, used to communicate with the terminal devices. The access network devices include, but are not limited to, base stations (base transceiver stations (BTS), Node B, evolved Node B (eNodeB) / eNB, or the next generation Node B (gNodeB) / gNB), transmission reception points (TRPs), base stations evolved from the 3rd generation partnership project (3GPP), access nodes in wireless fidelity (Wi-Fi) systems, wireless relay nodes, wireless backhaul nodes, etc. The base stations can be: macro base stations, micro base stations, pico base stations, small cells, relay stations, etc. Multiple base stations can support networks using the same access technology or networks using different access technologies. A base station can contain one or more co-located or non-co-located transmission and reception points. The access network equipment can also be a radio controller, centralized unit (CU), and / or distributed unit (DU) in a cloud radio access network (CRAN) scenario. The access network equipment can also be a server, etc. For example, the network equipment in V2X technology can be a roadside unit (RSU). The following description uses a base station as an example to illustrate the access network equipment. A base station can communicate with a terminal device, or it can communicate with a terminal device through a relay station. A terminal device can communicate with multiple base stations in different access technologies. The core network equipment is used to implement functions such as mobility management, data processing, session management, policy and billing. The names of the equipment implementing core network functions may differ in systems using different access technologies; this application does not limit this. Taking the 5th generation (5G) mobile communication technology system as an example, the core network equipment includes: access and mobility management function (AMF), session management function (SMF), policy control function (PCF) or user plane function (UPF), etc.

[0071] In the CU-DU architecture, access network equipment can include one or more logical network elements such as CU, DU, CU-control plane (CP), CU-user plane (UP), or radio unit (RU). CU and DU can be configured separately or included in the same network element, such as in a baseband unit (BBU). RU can be included in radio equipment or radio units, such as in a remote radio unit (RRU), active antenna unit (AAU), or remote radio head (RRH).

[0072] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an open RAN (ORAN) system, CU can also be called open CU (open CU, O-CU), DU can also be called open DU (open DU, O-DU), CU-CP can also be called open CU-CP (open CU-CP, O-CU-CP), CU-UP can also be called open CU-UP (open CU-CP, O-CU-UP), and RU can also be called open RU (open RU, O-RU). For ease of description, the embodiments of this application use CU, CU-CP, CU-UP, DU, and RU as examples. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in the embodiments of this application can be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

[0073] Optionally, in various embodiments of this application, if the network device is a distributed architecture, such as the network device including CU and DU, or including CU-CP, CU-UP and DU, then the network device sends information to the UE, specifically the DU included in the network device sends information to the UE; the network device receives information from the UE, specifically the DU included in the network device receives information from the UE.

[0074] In this application embodiment, the communication device used to implement the network device function can be a network device itself, or it can be a device capable of supporting the network device in implementing that function, such as a chip system. This device can be installed within the network device. In the technical solutions provided in this application embodiment, the example of a network device being used to implement the network device function is used to describe the technical solutions provided in this application embodiment.

[0075] Sensing, in this context, refers to the ability to detect parameters of targets in the physical environment, such as their position and velocity. It can be understood that sensing devices detect targets by emitting electromagnetic waves and analyzing the echo signals reflected from objects. In this sense, sensing can also be called detection.

[0076] A sensing signal is a signal used to sense (or detect) a target (or object). Sensing signals are also called detection signals, linear frequency modulated signals, radar signals, radar sensing signals, radar detection signals, or environmental sensing signals, etc. Sensing signals can be pulse signals or signals from wireless communication systems. For example, a sensing signal can be an orthogonal frequency division multiplexing (OFDM) signal obtained by modulating a specific sequence on a subcarrier. This specific sequence can be any of the following sequences: Zadoff-Chu sequence (ZC sequence), pseudo-random sequence, or predefined sequence. Pseudo-random sequences include any of the following sequences: longest linear feedback shift register sequence (m-sequence) or Gold sequence. Predefined sequences can be, for example, random data symbols, such as random data symbols modulated by quadrature phase shift keying (QPSK) or quadrature amplitude modulation (QAM).

[0077] Communication signals are signals transmitted between communication devices for the purpose of communication. For example, communication signals may include signals transmitted between network devices and terminal devices. Communication signals are, for example, carried on the physical downlink shared channel (PDSCH).

[0078] An echo signal is a signal generated when a sensed signal is reflected by a target. Both the echo signal and the sensed signal can reflect the parameters of the target. For example, the time delay of the echo signal relative to the sensed signal can reflect the distance of the target relative to the transmitter, and the Doppler shift of the echo signal relative to the sensed signal can reflect the velocity of the target.

[0079] Communication-sensing fusion signals, also known as synthetic-sensing fusion signals, synthetic signals, or integrated synthetic-sensing signals, are signals used for both communication and sensing. When used for communication, the fusion signal carries the communication data or reference signal sequence that needs to be transmitted between communication devices. When used for sensing, the fusion signal can be understood as being used to sense (or detect) targets.

[0080] A target can be any tangible object in the environment capable of reflecting electromagnetic waves, such as mountains, forests, or buildings, and can also include mobile objects such as vehicles, drones, pedestrians, and terminal devices. A target can also be referred to as a sensed target, a detected target, a sensed object, a detected object, or a sensed device, etc., and this application does not limit the terminology. For electromagnetic sensing, a target can generally be modeled as at least one scattering point (also called a scattering center), and the process of a target reflecting, scattering, or diffracting electromagnetic waves can be equivalent to the process of at least one scattering point reflecting, scattering, or diffracting electromagnetic waves. For point targets, the target can be modeled by one scattering point; for extended targets, the target can be modeled by multiple scattering points.

[0081] Communication-sensing integration is a key technology in next-generation wireless communication networks. It aims to merge wireless communication and sensing functions into a single system, utilizing the various propagation characteristics of wireless signals to achieve sensing functions such as target localization, detection, imaging, and identification. This allows for the acquisition of information about the surrounding physical environment, the enhancement of communication capabilities, and a better user experience. For example, a first device transmits a signal for sensing, and a second device (or the first device) receives the echo signal reflected from the target in the environment. For instance, the time delay of the echo signal relative to the signal used for sensing can reflect the distance to the target; the Doppler shift of the echo signal relative to the signal used for sensing can reflect the speed of the target, etc.

[0082] For sensing, based on the different senders and receivers of the sensing signal, sensing modes can be divided into two types: single-site sensing and dual-site sensing. Single-site sensing, also known as self-transmitting and self-receiving mode, refers to the same device sending the sensing signal and receiving the echo signal reflected from the target, as shown in Figure 1, where both the sending and receiving devices are device 1. Dual-site sensing, also known as A-transmitting and B-receiving mode or self-transmitting and other-receiving mode, refers to different devices sending the sensing signal and receiving the echo signal reflected from the target, as shown in Figure 2, where the sending device is device 2 and the receiving device is device 3. Figures 1 and 2 both use a vehicle as an example of the sensing target (or scatterer). Typical single-site sensing scenarios include base station self-transmitting and self-receiving sensing mode and UE self-transmitting and self-receiving sensing mode; typical dual-site sensing scenarios include base station A-transmitting and base station B-receiving sensing mode, base station-transmitting and UE-receiving sensing mode, and UE-transmitting and base station-receiving sensing mode, etc.

[0083] In collaborative sensing scenarios, each sensing node can send point cloud information to the fusion center. The fusion center can perform point cloud fusion based on the point cloud information corresponding to the same sensing target in the received point cloud information. For example, the sensing target can be identified based on the fusion result, and the path of the sensing target can be determined.

[0084] If the target is small, multiple sensing nodes may perceive the same target point (or scattering point) when sensing it. In this case, the fusion center fuses the point cloud information corresponding to the target point, resulting in a more accurate fusion result. Figure 3 illustrates one such fusion result. The horizontal axis of Figure 3 represents the X-axis of the Cartesian coordinate system, and the vertical axis represents the Y-axis. Figure 3 includes two sets of points: for example, the "\" shaped point set represents point cloud information from one sensing node, and the " / " shaped point set represents point cloud information from another sensing node. The intersection of these two sets of points is the fusion result, representing the location of the target.

[0085] However, the perceived target may be large in size; for example, a large perceived target is called an extended target. Vehicles and ships are examples of extended targets. If the sensing nodes are located at different positions on the extended target, they may perceive different target points on that extended target. For example, if the extended target is a vehicle, a sensing node located on the right side of the vehicle may perceive target points on the right side of the vehicle, while a sensing node located behind the vehicle may perceive target points on the rear side. In this case, the point cloud information of the vehicle obtained by the fusion center from multiple sensing nodes may correspond to different target points on the vehicle. When the fusion center fuses this point cloud information, the fusion result may contain biases. For example, refer to Figure 4, which shows an example of a fusion result. The horizontal axis of Figure 4 represents the X-axis of the Cartesian coordinate system, and the vertical axis represents the Y-axis. Figure 4 includes two sets of points; for example, the "\" shaped point set represents the point cloud information from one sensing node, and the " / " shaped point set represents the point cloud information from another sensing node. The circles at the bottom of Figure 4 represent the fusion result. The actual position coordinates of the vehicle can be seen from the fusion result in Figure 3. Therefore, as shown in Figure 4, there is a deviation in the fusion result of these two sets of points, which causes the position of the vehicle determined by the fusion node to be offset relative to the actual position of the vehicle.

[0086] Therefore, in this embodiment, the first sensing node can determine the deviation of the first sensing result based on the first information, and thus correct the value of the first parameter based on the deviation, thereby improving the accuracy of the first parameter. The sensing center performs point cloud fusion based on the corrected value of the first parameter, which is beneficial to improving the sensing accuracy.

[0087] The sensing method provided in this application can be applied to fourth-generation (4G) communication systems, such as Long Term Evolution (LTE) systems, and also to fifth-generation (5G) communication systems, such as 5G New Radio (NR) systems, or to future communication systems. The method provided in this application can also be applied to Bluetooth systems, Wireless Fidelity (Wi-Fi) systems, Long Range Radio (LoRa) systems, or vehicle-to-everything (V2X) systems. The method provided in this application can also be applied to satellite communication systems, wherein the satellite communication system can be integrated with the aforementioned communication systems.

[0088] Please refer to Figure 5, which is a schematic diagram of a scenario involving integrated communication and sensing. Figure 5 includes a network device and multiple UEs. For example, UE1 and the network device adopt a dual-site sensing mode, where UE1 is the transmitter of the sensing signal (or, fusion sensing signal), and the network device is the receiver of the echo signal of the sensing signal (or, fusion sensing signal). UE3 and the network device also adopt a dual-site sensing mode, where the network device is the transmitter of the sensing signal (or, fusion sensing signal), and UE3 is the receiver of the echo signal of the sensing signal (or, fusion sensing signal). The network device and UE2 are communicating and can transmit communication signals. Figure 5 also includes a single-site sensing mode, where the network device's sensing of scatterer 3 and scatterer 5 is performed in a single-site sensing mode. In addition, in Figure 5, the network device can send communication signals to UE4, and the network device can also send sensing signals or fusion signals. UE4 can receive the communication signals. If the network device sends a fusion signal, then UE4 can also receive the fusion signal. The network device adopts a single-site sensing mode, and the network device can also receive the echo signal reflected by the scatterer 4 from the sensing signal or fusion signal.

[0089] Figure 5 uses UE3 as a vehicle and scatterer 3 as a human body as an example. There are no restrictions on the types of other UEs and scatterers. Figure 5 uses one network device as an example; in reality, there may be many more network devices.

[0090] Please refer to Figure 6, which is a schematic diagram of an application scenario according to an embodiment of this application. Figure 6 includes sensing nodes 1 to 3, and a fusion center. The three sensing nodes can perform sensing and send the obtained sensing data to the fusion center; the fusion center can combine the sensing data of the three sensing nodes to determine the sensing result. The scenario shown in Figure 6 can be considered a collaborative sensing scenario. Collaborative sensing can involve multiple access network devices collaborating, multiple UEs collaborating, or one or more access network devices and one or more UEs collaborating, etc., and is not specifically limited. The three sensing nodes shown in Figure 6 are taken as access network devices, but are not limited to this. For example, any one of the three sensing nodes can be an access network device or a UE. In addition, Figure 6 shows an example of a fusion center existing independently of the sensing nodes, but is not limited to this. For example, the fusion center can also be implemented by one of the sensing nodes.

[0091] The method provided in the embodiments of this application is described below with reference to the accompanying drawings. In various embodiments of this application, the signals used for sensing include, for example, sensing signals and / or sensor fusion signals. In various embodiments of this application, the fusion center is, for example, an access network device or a UE. The access network device can be any access network device participating in sensing, and the UE can be any UE participating in sensing; or, the access network device or UE can be a specific device that does not participate in the transmission and reception of sensing signals, but is only responsible for processing the sensing data reported by each sensing node. Alternatively, the fusion center is, for example, a core network device, which is, for example, a sensing network element. The sensing network element is, for example, a sensing function (SF) or a sensing service function, etc., and the name is not limited. In various embodiments of this document, "network element" can also be replaced with "entity" or "functional entity". For example, a sensing network element can also be called a sensing entity, a sensing function entity, or a sensing function network element, etc., and "sensing network element" will be used as an example below.

[0092] Optionally, the fusion center can be used to perceive the target, such as determining the location of the target or reconstructing the environment of the target, without limitation. This application embodiment does not limit the deployment of the fusion center. For example, the fusion center can be deployed in the core network or in the access network, without limitation. For example, the fusion center can also be a network management platform or network management equipment, etc. It should be understood that in future communication systems, the functional entity used for perceiving the target can still be called a fusion center, or it can have other names; this application embodiment does not limit this.

[0093] In the accompanying drawings corresponding to the various embodiments of this application, all steps indicated by dashed lines are optional steps.

[0094] The various embodiments described herein can be applied to the network architecture shown in any of the figures 1, 2, 5, and 6. For example, any sensing node described in any of the embodiments herein can be device 1 in Figure 1; or, any sensing node described in any of the embodiments herein can be device 3 in Figure 2; or, any sensing node described in any of the embodiments herein can be network device or UE3 in Figure 5; or, any sensing node described in any of the embodiments herein can be any sensing node in Figure 6, and the fusion center described in any of the embodiments herein can be the fusion center in Figure 6.

[0095] Please refer to Figure 7, which is a flowchart of a sensing method provided in an embodiment of this application.

[0096] S701. At least one sensing node sends at least one sensing result. Correspondingly, the fusion center receives the at least one sensing result. For example, the at least one sensing result corresponds one-to-one with the at least one sensing node. The at least one sensing node may include, for example, a first sensing node and a second sensing node. The sensing result sent by the first sensing node is called the first sensing result, and the sensing result sent by the second sensing node is called the second sensing result. Figure 7 uses this as an example.

[0097] Wherein, if the number of the at least one sensing node is greater than 1, the scenario is a collaborative sensing scenario, and all at least one sensing node are nodes participating in collaborative sensing; if the number of the at least one sensing node is 1, the scenario is not a collaborative sensing scenario. That is, the embodiments of this application can be applied to both collaborative and non-collaborative sensing scenarios.

[0098] The at least one sensing node may be determined by the fusion center. Optionally, the at least one sensing node may have overlapping sensing areas, meaning that all at least one sensing node can sense the overlapping area. Optionally, the parameters used by the at least one sensing node for sensing may be configured by the fusion center or predefined by the protocol. These parameters may include, for example, one or more of the time-domain, frequency-domain, code-domain, or spatial-domain information of the sensing resources. For a sensing node, after experiencing a sensing frame, a sensing result can be obtained, and the sensing node can send the sensing result to the fusion center. The sensing result sent by a sensing node to the fusion center may include, for example, the point cloud information obtained by the sensing node. Optionally, all at least one sensing result may include point cloud information. For example, the first sensing result may include the first point cloud information obtained by the first sensing node. The point cloud information obtained by a sensing node may include one or more of the following: the position parameters, radial velocity, signal-to-noise ratio (SNR), received signal strength, or error parameters of the sensing target corresponding to the point cloud information. The error parameters may include one or more of the following: error covariance parameters, error elliptic parameters, or error variance parameters.

[0099] For example, a sensing node can send all the point cloud information it obtains to the fusion center, or a sensing node can send point cloud information that meets certain conditions to the fusion center, such as those indicated by the fusion center, without any restrictions.

[0100] The first perception result may include a first value, which is the value of a first parameter. The first parameter may include, for example, one or more of the following: error covariance parameter, signal-to-noise ratio, error elliptic parameter, error variance parameter, or received signal strength. In addition, the first parameter may include other parameters, without limitation. Optionally, the first parameter may be included in the first point cloud information, or the first parameter and the first point cloud information may be two different pieces of information.

[0101] S702, the fusion center sends the first information. Correspondingly, the first sensing node receives the first information.

[0102] The first information can be used to determine the deviation of the first perception result. The first information is, for example, determined by the fusion center based on at least one perception result. If this embodiment is applied to a collaborative perception scenario, optionally, the fusion center can send information to some or all of the at least one perception node. The information sent by the fusion center to any one perception node can be used to determine the deviation of the perception result sent by that perception node in S701. This information can be determined based on at least one perception result. The information sent by the fusion center can be associated with a perception result (e.g., point cloud information); for example, a perception result can be associated with one piece of information, or a perception result can be associated with a deviation. For different perception nodes, the deviation of the perception result may be the same or different. For example, the at least one perception node also includes a second perception node. The second perception node sends a second perception result to the fusion center in S701, and the fusion center can send second information to the second perception node in S702. The second information can be used to determine the deviation of the second perception result, as illustrated in Figure 7. The deviation of the first perception result and the deviation of the second perception result can be the same or different.

[0103] For at least one sensing node, the deviation of the sensing result indicated by the fusion center to any one of the sensing nodes may include the positional deviation of the sensing target corresponding to the sensing result of that node. This positional deviation may be the deviation between the position of the sensing target corresponding to the sensing result of that node and a reference position corresponding to the sensing result of that node. Optionally, the reference position may be determined based on the contour of the sensing target corresponding to the sensing result of that node. This reference position may be, for example, the geometric center or centroid of the sensing target, or it may be another point on the sensing target. Optionally, the position of the sensing target corresponding to the sensing result of that node may be, for example, the position of the target point corresponding to the sensing result of that node. This target point may be located on the sensing target corresponding to the sensing result, or it may be understood that when that sensing node performs sensing on the sensing target, it senses or detects the target point.

[0104] For example, the deviation of the first perception result indicated by the first information may include the positional deviation of the perceived target corresponding to the first perception result. This positional deviation can be the deviation between the position of the perceived target corresponding to the first perception result and the reference position corresponding to the first perception result. The position of the perceived target corresponding to the first perception result is, for example, the position of the target point corresponding to the first perception result. The target point corresponding to the first perception result may be located on the perceived target, or it can be understood as the target point perceived by the first perception node when performing perception on the perceived target. The reference position corresponding to the first perception result can be determined based on the outline of the perceived target. This reference position may be, for example, the geometric center or centroid of the perceived target, or it may be another point on the perceived target. Taking the reference position as the geometric center of the perceived target as an example, the deviation between the target point corresponding to the first perception result and the geometric center of the perceived target is the positional deviation.

[0105] For example, the deviation of the second perception result indicated by the second information may include the positional deviation of the perceived target corresponding to the second perception result. This positional deviation can be the deviation between the position of the perceived target corresponding to the second perception result and the reference position corresponding to the second perception result. The position of the perceived target corresponding to the second perception result is, for example, the position of the target point corresponding to the second perception result. The target point corresponding to the second perception result may be located on the perceived target, or it can be understood as the target point perceived by the second perception node when performing perception on the perceived target. The reference position can be determined based on the outline of the perceived target corresponding to the second perception result. The reference position corresponding to the second perception result may be, for example, the geometric center or centroid of the perceived target, or it may be another point on the perceived target. Taking the reference position as the geometric center of the perceived target as an example, the deviation between the target point corresponding to the second perception result and the geometric center of the perceived target is the positional deviation. The perceived target corresponding to the first perception result and the perceived target corresponding to the second perception result may be the same target or different targets.

[0106] The processing methods are similar for both the fusion center and any of the sensing nodes. Therefore, this application will use the first sensing node, the first sensing result, and the first information as examples to illustrate the process.

[0107] If the position of the target point corresponding to the first perception result coincides with the reference position corresponding to the first perception result, it indicates that there is no positional deviation in the first perception result; however, if the position of the target point does not coincide with the reference position, it indicates that there is a positional deviation in the first perception result. For example, if the reference position is the intersection position shown in Figure 3, and the position of the target point corresponding to the first perception result is the position of the circle shown at the bottom of Figure 4, then the deviation between these two positions is the positional deviation.

[0108] The first information can be used in different ways to enable the first sensing node to determine the deviation of the first sensing result based on the first information.

[0109] As a first optional implementation of the first information, the first information may indicate a deviation of the first sensing result. This deviation, for example, is the distance between the location of the target point corresponding to the first sensing result and the reference location corresponding to the first sensing result. For instance, the deviation indicated by the first information may include one or more of the following: longitude deviation, latitude deviation, or altitude deviation between the two locations. This indication method is relatively explicit, and the first sensing node can directly determine the deviation of the first sensing result based on the first information.

[0110] In a first optional implementation of the first information, the fusion center can first determine the deviation of the first perception result, and then indicate the deviation through the first information. As an optional implementation of the fusion center determining the deviation, the fusion center can determine the contour of the perceived target corresponding to the first perception result, and then determine the deviation based on the contour. Taking the reference position corresponding to the first perception result as the position of the geometric center of the perceived target corresponding to the first perception result as an example, for instance, the fusion center can determine the position of the target point corresponding to the first perception result and the position of the geometric center of the perceived target based on the contour, and thus determine the deviation of the first perception result based on these two positions; for example, the deviation between these two positions is the deviation itself.

[0111] In step S701, the fusion center receives at least one sensing result. Optionally, the fusion center can determine the contour of the sensing target corresponding to the first sensing result based on the at least one sensing result. As an optional method for the fusion center to determine the contour, it can cluster the at least one sensing result and determine the contour of the sensing target based on the clustering results. Taking at least one point cloud information as an example, the fusion center can cluster the at least one point cloud information, dividing it into different categories. Each category can correspond to a sensing target. Thus, the fusion center can determine the sensing target corresponding to the first sensing node and determine the contour of the sensing target based on the clustering results. Various clustering methods can be used, such as nearest neighbor interpolation, density-based spatial clustering of applications with noise (DBSCAN), or k-means clustering, etc., without specific limitations. For example, referring to Figure 8, one clustering method is shown, where the horizontal axis is the X-axis and the vertical axis is the Y-axis. The circles in Figure 8 represent clustering results, each corresponding to a sensing target. The points within the circles represent points belonging to that cluster among at least one point cloud indicator. Based on the positions of the points within the circles, the outline of the sensing target can be estimated. For example, the length and width of the sensing target can be determined based on the points within the circles.

[0112] Alternatively, as another possible way for the fusion center to determine the contour, the fusion center can input the at least one point cloud information into a first model, which can output the contour information. The first model can be, for example, an artificial intelligence (AI) model, or other types of models, without limitation. The first model can be trained by the fusion center, or it can be trained by a third party and then deployed at the fusion center.

[0113] As a second optional implementation of the first information, the first information may indicate the outline of the perceived target corresponding to the first perception result. For example, if the perceived target is a vehicle, the first information may indicate the outline information of the vehicle. Based on the outline information, the first perception node can determine the position of the target point corresponding to the first perception result, and determine the reference position corresponding to the first perception result. Thus, the first perception node can determine the deviation of the first perception result based on the position of the target point and the reference position.

[0114] In a second alternative implementation of the first information, the fusion center may first determine the contour, thereby indicating the contour through the first information. For details on how the fusion center determines the contour, please refer to the relevant description above.

[0115] As a third optional implementation of the first information, the first information may indicate the size of the sensing target corresponding to the first sensing result and the direction of movement of the sensing target. For example, if the sensing target is a vehicle, the first information may indicate the length, width, and height of the vehicle, as well as the vehicle's direction of movement. Based on the size and / or direction of movement, the first sensing node can determine the position of the target point corresponding to the first sensing result, and can also determine a reference position corresponding to the first sensing result. Thus, the first sensing node can determine the deviation of the first sensing result based on the position of the target point and the reference position.

[0116] In a third optional implementation of the first information, the fusion center can determine the size of the sensing target corresponding to the first sensing result and the direction of movement of the sensing target, thereby indicating the size of the sensing target and the direction of movement of the sensing target through the first information. Optionally, the fusion center can determine the size of the sensing target and the direction of movement of the sensing target based on the outline of the sensing target; the method by which the fusion center determines the outline can be found in the relevant description above.

[0117] Alternatively, the size of the perceived target can be a preset size. For example, if the perceived target is a vehicle, different models have preset sizes, such as one model measuring 5×2×1.6 meters and another measuring 13×2.6×3 meters. The fusion center can determine the corresponding size based on the vehicle model of the perceived target. The direction of movement of the perceived target can be determined, for example, based on its outline. For details on how the fusion center determines this outline, please refer to the relevant introduction above.

[0118] In addition, the first message can be indicated in other ways, and there are no restrictions on this.

[0119] S703, the first sensing node sends the second value. Correspondingly, the fusion center receives the second value.

[0120] The second value can be the value of the first parameter. In the first perception result, the value of the first parameter is the first value, while in S703, the value of the first parameter is the second value. The first perception result and the second value can correspond to the same perception target.

[0121] For example, the first perception result includes a first value of a first parameter, which is the error covariance parameter. The first perception result is specific to the first perceived target. After receiving the first information, such as information indicating the outline of the perceived target, the first perception node determines a second value of the error covariance parameter based on the first information. Alternatively, it can be understood that after receiving the first information, the first perception node updates the error covariance parameter and reports it again to the fusion center.

[0122] Optionally, the second value can be determined by the first sensing node based on the first value and the first information. Alternatively, it can be understood that if there is a positional deviation in the first sensing result, the value of the first parameter included in the first sensing result may also be deviated. The first sensing node can correct or update the value of the first parameter based on the first information to reduce the deviation of the first parameter; the corrected or updated value of the first parameter is the second value.

[0123] The first sensing node can send third information, which may include the second value. Optionally, the third information may also include indication information, which indicates that the second value is an updated sensing result. Thus, the fusion center can determine, based on this indication information, that the second value is an updated value of the first parameter, or that the second value is used to update the first sensing result. For example, the fusion center can use the second value to replace the value of the first parameter in the first sensing result.

[0124] There are multiple ways to implement the first parameter. When the first parameter is different, the way the first sensing node determines the second value may be the same or different. The following uses several implementations of the first parameter as examples to illustrate how the first sensing node can determine the second value.

[0125] Taking the first parameter, which includes the error covariance parameter, as an example, the error covariance is calculated as follows:

[0126] (Formula 1)

[0127] Where r represents the distance between the sensing target and the first sensing node, and θ represents the angle between the sensing target and the first sensing node, where r and θ are determined by the first sensing node through sensing. This represents the variance estimate of the distance estimation error for the first sensing node. This represents the variance estimate of the angle estimation error of the first sensing node. and / or It can be related to perceived resolution. Optionally, it can be made... Where c represents the speed of light, B represents the bandwidth of the signal used for sensing, and θ 3dB This represents the 3-decibel (dB) beamwidth of the first sensing node.

[0128] The first sensing node can determine a second distance based on the first information and the first distance, and determine a second angle based on the first information and the first angle. Therefore, based on the second distance, the second angle, the first distance, and the first angle, a second value can be determined. Optionally, the first distance can be the distance between the first sensing node and the detected (or perceived) target, and the first angle is the angle between the detected (or perceived) target and the first sensing node. The first value of the first parameter can be determined based on the first distance and the first angle. This can also be understood as the first sensing node correcting the first distance based on the first information, resulting in the second distance; and the first sensing node correcting the first angle based on the first information, resulting in the second angle. Thus, the first sensing node can obtain the second value based on the corrected distance, the corrected angle, the original distance, and the original angle.

[0129] For example, let r represent the first distance and θ represent the first angle. If r and θ do not correspond to a Cartesian coordinate system, the first sensing node can transform both r and θ to a Cartesian coordinate system. For example, after the transformation, we get x = r × cos(θ) and y = r × sin(θ). The first information indicates the X-axis deviation and the Y-axis deviation, where the X-axis deviation is δx and the Y-axis deviation is δy. Then, the first sensing node can deduce the second distance and / or the second angle based on (x + δx, y + δy). The second distance is, for example, r′, and the second angle is, for example, θ′. Substituting r′ and θ′ into Formula 1, the first sensing node can determine the second value of the error covariance.

[0130] For example, the coordinates of the first sensing node are (150, 0), the actual coordinates of the sensed target are (-0.89, 67.43), and the deviation indicated by the first information is (2.5, 1). When the first sensing node detects the sensed target, it actually detects information that has already been deviated from its intended value. For example, if the first sensing node determines r to be 163.4 m and θ to be 2.7 rad, substituting r and θ into Formula 1, the first value of the error covariance is... After correction according to the deviation (2.5,1), r′ is obtained as 165.2m and θ′ as 2.72rad. Substituting r′ and θ′ into Formula 1, the second value of the error covariance is obtained.

[0131] Taking the example of the first parameter including the error variance parameter, this error variance parameter can include the diagonal elements of the error covariance matrix determined by the first sensing node. For example, the first sensing node can determine a new error covariance parameter based on the first value and the first information, as described above. The new error covariance parameter determined by the first sensing node according to Formula 1 is, for example, an error covariance matrix, and the diagonal elements of this matrix can be the error variance parameter, the value of which is the second value.

[0132] Taking the error ellipse parameter as an example, the first sensing node can determine a new error covariance parameter based on the first value and the first information, as described above. The new error covariance parameter determined by the first sensing node according to Formula 1 is, for example, an error covariance matrix. The diagonal elements of this error covariance matrix can be error variance parameters, corresponding to the error variance in at least one dimension. For example, this error variance parameter can correspond to the error variance on at least one axis, such as the X-axis, Y-axis, or Z-axis. The first sensing node can determine the error ellipse parameter based on this error variance and the deviation indicated by the first information. For example, refer to Figure 9 for an example of error variance. Figure 9 uses the error variance parameter corresponding to the error variance of the X-axis and Y-axis as an example. For instance, the error variance of the X-axis is r1 (as shown in Figure 9, the semi-major axis r1), and the error variance of the Y-axis is r2 (as shown in Figure 9, the semi-minor axis r2).

[0133] Taking the signal-to-noise ratio (SNR) as an example, where the first parameter is related to parameters such as path loss (PL), the first sensing node can determine the first path loss based on the first information and the first value. Based on the first path loss, a second value for the SNR can be determined. For instance, if the first sensing node determines the deviation of the first sensing result based on the first information, a new path loss, called the first path loss, can be determined based on this deviation. The SNR value can then be updated based on the first path loss, for example, to the second value.

[0134] Taking the first parameter, which includes the received signal strength, as an example, the received signal strength can be related to parameters such as path loss. The formula for calculating path loss is, for example: PathLoss=28.0+22*log10(d 3D )+20*log10(f c )

[0135] (Formula 2)

[0136] Where PathLoss represents path loss, f c d represents frequency. 3DThis represents the three-dimensional distance between the sensing target and the sensing signal receiver (e.g., the first sensing node). The first sensing node can determine the second path loss based on the location information corresponding to the first sensing result. Furthermore, based on the first information and the location information corresponding to the first sensing result, it can determine the third path loss. Therefore, the first sensing node can determine a second value of the received signal strength based on the second and third path losses. Taking the received signal strength as characterized by the reference signal receiving power (RSRP) as an example, this second value is represented as RSRP2, for example, RSRP2 = RSRP1 - PL1 - PL2. Here, RSRP1 represents the received signal strength corresponding to the first sensing result, PL1 represents the second path loss, and PL2 represents the third path loss.

[0137] Taking the received signal strength characterized by RSRP as an example. For instance, suppose the RSRP value (i.e., the first value) included in the first sensing result is 160 dBm, and the distance between the sensing target determined by the first sensing node and the first sensing node is 163.4 m. After correction based on the first information, the distance between the sensing target determined by the first sensing node and the first sensing node is 165.2 m. Before and after correction, the difference in path loss for a one-way path is PL1 - PL2 = -0.1047 dB. Here, PL1 represents the path loss before correction, and PL2 represents the path loss after correction. For example, if the first sensing node uses a self-transmitting and self-receiving sensing mode, the signal used for sensing travels a two-way path, and the difference in path loss before and after correction is 0.2094 dB. That is, after correction, the path loss increases. According to RSRP2 = RSRP1 - PL1 - PL2, the second value of RSRP can be determined to be 159.7906 dBm.

[0138] If the fusion center sends information indicating deviation to multiple sensing nodes in S702, then in S703, these multiple sensing nodes can also send the correction value of the first parameter to the fusion center. For example, in S701, the second sensing node sends a second sensing result to the fusion center, which includes a third value, the value of the first parameter. In S702, the fusion center sends second information to the second sensing node, indicating the deviation of the second sensing result. The second sensing node determines a fourth value of the first parameter based on the second information and can send the fourth value to the fusion center, as shown in Figure 7. The way the second sensing node determines the fourth value is similar to the way the first sensing node determines the second value, and will not be elaborated further.

[0139] Optionally, the method may also include S704, whereby the fusion center performs point cloud fusion based on the second value.

[0140] For example, the fusion center can replace the value of the first parameter included in the first perception result with a second value (i.e., replace the first value with the second value), thereby performing point cloud fusion using the replaced first perception result (e.g., referred to as perception result 1). Optionally, if the fusion center receives multiple correction values, it can perform point cloud fusion based on these multiple correction values. For example, if the fusion center also receives a fourth value, it can perform point cloud fusion based on the fourth value and the second value, as illustrated in Figure 7. For example, the fusion center performing point cloud fusion using the replaced first perception result may include the fusion center performing point cloud fusion using N perception results A, which come from N perception nodes. These N perception results A may correspond to N perception results B in the at least one perception result, but the value of the first parameter can be replaced in relation to the N perception results B in the at least one perception result. The N perception nodes include a first perception node, one of the N perception results B is the first perception result, and one of the N perception results A is perception result 1. N is a positive integer.

[0141] For example, in step S701, the fusion center receives N sensing results from the N sensing nodes, denoted as N sensing results A. The fusion center sends corresponding information to each of the N sensing nodes to indicate the deviation. The N sensing nodes correct the value of the first parameter based on the received information and send the corrected value of the first parameter to the fusion center. As a result, the fusion center replaces the value of the first parameter in the N sensing results B, thus obtaining the N sensing results A.

[0142] The N perception results A can correspond to the same perception target, therefore the fusion center can perform point cloud fusion on the N perception results A corresponding to the same perception target. For example, one method of point cloud fusion is as follows:

[0143] Formula 3 takes N=3 as an example. For instance, the N sensing results A are sensing result 1 from the first sensing node, sensing result 2 from the second sensing node (sensing result 2 is, for example, the second sensing result after replacing the value of the first parameter), and sensing result 3 from the third sensing node (sensing result 3 is, for example, the third sensing result after replacing the value of the first parameter; the third sensing result is the sensing result sent by the third sensing node to the fusion center in S701). L represents the fused sensing result. L1 represents the coordinates indicated by sensing result 1, L2 represents the coordinates indicated by sensing result 2, and L3 represents the coordinates indicated by sensing result 3. This represents the value of the error covariance included in perception result 1. This represents the value of the error covariance included in perception result 2. This represents the value of the error covariance included in perception result 3, where These are all correction values ​​for the error covariance.

[0144] For example, if the first parameter is the error covariance parameter, then the fusion center can be used to perform point cloud fusion using Formula 3.

[0145] In this embodiment, the first sensing node can determine the deviation of the first sensing result based on the first information, and then correct the value of the first parameter based on the deviation, thereby improving the accuracy of the first parameter. The sensing center performs point cloud fusion based on the corrected value of the first parameter, which helps to improve the sensing accuracy.

[0146] Figure 10 shows a schematic diagram of a device provided in an embodiment of this application. The device 1000 may be the fusion center or its circuit system as shown in the embodiment of Figure 7, used to implement the method corresponding to the fusion center in the above method embodiments. Alternatively, the device 1000 may be the first sensing node or its circuit system as shown in the embodiment of Figure 7, used to implement the method corresponding to the first sensing node in the above method embodiments. For example, one type of circuit system may be a chip system.

[0147] Since the device 1000 in the embodiments of this application can implement the sensing method, the device 1000 can also be called a sensing device. In implementation, the device 1000 may have sensing function but no communication function, or it may have both sensing and communication functions. If the device 1000 has communication function, it may also be called a communication device, etc., without limitation.

[0148] The device 1000 includes at least one processor 1001. The processor 1001 can be used for internal processing within the device to implement certain control processing functions. Optionally, the processor 1001 includes instructions. Optionally, the processor 1001 can store data. Optionally, different processors can be independent devices, located in different physical locations, or located on different integrated circuits. Optionally, different processors can be integrated into one or more processors, for example, integrated onto one or more integrated circuits.

[0149] Optionally, the device 1000 includes one or more memories 1003 for storing instructions. Optionally, the memories 1003 may also store data. The processor and the memories may be separate or integrated together.

[0150] Optionally, the device 1000 includes a communication line 1002 and at least one communication interface 1004. Since the memory 1003, communication line 1002, and communication interface 1004 are all optional, they are all represented by dashed lines in FIG10.

[0151] Optionally, device 1000 may further include a transceiver and / or an antenna. The transceiver can be used to send information to or receive information from other devices. The transceiver may be referred to as a transceiver unit, transceiver circuit, input / output interface, etc., and is used to implement the transmission and reception functions of device 1000 via the antenna. Optionally, the transceiver includes a transmitter and a receiver. For example, the transmitter can be used to generate a radio frequency (RF) signal from a baseband signal, and the receiver can be used to convert the RF signal back into a baseband signal.

[0152] The processor 1001 may include a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of programs according to the present application.

[0153] The communication line 1002 may include a path for transmitting information between the aforementioned components.

[0154] Communication interface 1004 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), wired access network, etc.

[0155] The memory 1003 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 1003 may exist independently and be connected to the processor 1001 via communication line 1002. Alternatively, the memory 1003 may be integrated with the processor 1001.

[0156] The memory 1003 stores computer execution instructions for implementing the scheme of this application, and the processor 1001 controls the execution. The processor 1001 executes the computer execution instructions stored in the memory 1003, thereby implementing the steps performed by the fusion center or the first sensing node in the embodiment shown in FIG7.

[0157] Optionally, the computer execution instructions in the embodiments of this application may also be referred to as application code, and the embodiments of this application do not specifically limit this.

[0158] In a specific implementation, as one embodiment, the processor 1001 may include one or more CPUs, such as CPU0 and CPU1 in FIG10.

[0159] In a specific implementation, as one embodiment, device 1000 may include multiple processors, such as processor 1001 and processor 1005 in FIG. 10. Each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0160] When the device shown in Figure 10 is a chip, such as the chip of the fusion center or the chip of the first sensing node, the chip includes a processor 1001 (which may also include a processor 1005), a communication line 1002, and a communication interface 1004. Optionally, it may include a memory 1003. Specifically, the communication interface 1004 may be an input interface, pins, or circuits, etc. The memory 1003 may be a register, cache, etc. The processor 1001 and processor 1005 may be a general-purpose CPU, microprocessor, ASIC, or one or more integrated circuits for controlling the execution of a program for controlling the sensing method of any of the above embodiments.

[0161] This application embodiment can divide the device into functional modules according to the above method examples. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or software functional modules. The module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may exist in actual implementation. For example, when dividing the device into functional modules according to each function, Figure 11 is a schematic diagram of a device 1100. This device 1100 can be the fusion center or first sensing node involved in the above method embodiments, or a chip in the fusion center or the first sensing node. The device 1100 includes a processing unit 1102 and a transceiver unit 1101. Since the device 1100 in this application embodiment can implement the sensing method, the device 1100 can also be called a sensing device. In implementation, the device 1100 may have sensing functions but no communication functions, or it may have both sensing and communication functions. If device 1100 has communication function, it can also be called a communication device, etc., without limitation.

[0162] It should be understood that the device 1100 can be used to implement the steps performed by the fusion center or the first sensing node in the sensing method of the embodiments of this application. The relevant features can be referred to the embodiment shown in Figure 7 above, and will not be repeated here.

[0163] Optionally, the functions / implementation processes of the transceiver unit 1101 and processing unit 1102 in Figure 11 can be implemented by the processor 1001 in Figure 10 calling computer execution instructions stored in memory 1003. Alternatively, the functions / implementation processes of the processing unit 1102 in Figure 11 can be implemented by the processor 1001 in Figure 10 calling computer execution instructions stored in memory 1003, and the functions / implementation processes of the transceiver unit 1101 in Figure 11 can be implemented by the communication interface 1004 in Figure 10.

[0164] Optionally, when the device 1100 is a chip or circuit, the function / implementation process of the transceiver unit 1101 can also be implemented through pins or circuits. Optionally, the transceiver unit 1101 may include a transmitting unit and / or a receiving unit, wherein the transmitting unit is used to implement the transmitting function and the receiving unit is used to implement the receiving function; or, the transceiver unit 1101 may be an integral module capable of implementing the transmitting and / or receiving functions. Optionally, the transceiver unit 1101 may be implemented using a transceiver.

[0165] This application also provides a computer-readable storage medium storing a computer program or instructions that, when executed, implement the methods performed by the fusion center and / or the first sensing node in the aforementioned method embodiments. Thus, the functions described in the above embodiments can be implemented as software functional units and sold or used as independent products. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to it, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0166] This application also provides a computer program product comprising: computer program code, which, when run on a computer, causes the computer to perform the method executed by the fusion center and / or the first sensing node in any of the foregoing method embodiments.

[0167] This application also provides a processing apparatus, including a processor and an interface; the processor is used to execute the methods performed by the fusion center and / or the first sensing node involved in any of the above method embodiments.

[0168] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0169] The various illustrative logic units and circuits described in the embodiments of this application can be implemented or operate the described functions using a general-purpose processor, digital signal processor (DSP), ASIC, field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. The general-purpose processor can be a microprocessor; alternatively, it can be any conventional processor, controller, microcontroller, or state machine. The processor can also be implemented using a combination of computing devices, such as a digital signal processor and a microprocessor, multiple microprocessors, one or more microprocessors combined with a digital signal processor core, or any other similar configuration.

[0170] The steps of the methods or algorithms described in the embodiments of this application can be directly embedded in hardware, software units executed by a processor, or a combination of both. The software units can be stored in RAM, flash memory, ROM, erasable programmable read-only memory (EPROM), EEPROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium in the art. Exemplarily, the storage medium can be connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and storage medium can be disposed in an ASIC, which can be disposed in the terminal device. Optionally, the processor and storage medium can also be disposed in different components of the terminal device.

[0171] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0172] The contents of the various embodiments of this application can be referenced to each other. Unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other. The technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0173] It is understood that in the embodiments of this application, the fusion center and / or the first sensing node may execute some or all of the steps in the embodiments of this application. These steps or operations are merely examples. In the embodiments of this application, other operations or variations of various operations may also be performed. Furthermore, the steps may be performed in different orders as presented in the embodiments of this application, and it is not necessary to perform all the operations in the embodiments of this application.

Claims

1. A perception method, comprising: The method includes: Receive at least one perception result, the at least one perception result comes from at least one perception node, and the first perception result in the at least one perception result includes a first value, the first value being the value of a first parameter; Send first information, the first information being used to determine the deviation of the first perception result, the first information being determined based on the at least one perception result; Receive a second value, which is determined based on the first information and the first value.

2. The method of claim 1, wherein, The first perception result and the second value correspond to the same perception target.

3. The method according to claim 1 or 2, characterized in that, The at least one perception result is point cloud information.

4. The method according to any one of claims 1 to 3, characterized in that, Send the first message, including: Send the first information to the first sensing node.

5. The method according to any one of claims 1 to 4, characterized in that, The first parameter includes one or more of the following: error covariance parameter, signal-to-noise ratio, error elliptic parameter, error variance parameter, or received signal strength.

6. The method according to any one of claims 1 to 5, characterized in that, The deviation of the first perception result is the deviation between the position of the perceived target corresponding to the first perception result and the reference position.

7. The method according to claim 6, characterized in that, The reference position is determined based on the outline of the perceived target, which is the perceived target corresponding to the first perception result and the second value.

8. The method according to claim 6 or 7, characterized in that, The reference position is the geometric center of the perceived target.

9. The method according to claim 7 or 8, characterized in that, The method further includes: The contour of the perceived target is determined based on the at least one perception result.

10. The method according to claim 9, characterized in that, Determining the contour of the perceived target based on at least one perception result includes: Cluster the target points indicated by the at least one perception result, and determine the contour based on the clustering results; or, The at least one perception result is input into the first AI model to obtain the contour information output by the first AI model.

11. The method according to any one of claims 1 to 10, characterized in that, The first information is used to indicate the deviation; or, The first information is used to indicate the outline of the perceived target, and the perceived target is the perceived target corresponding to the first perception result and the second value; or, The first information is used to indicate the size of the perceived target and the direction of movement of the perceived target, wherein the perceived target is the perceived target corresponding to the first perception result and the second value.

12. The method according to claim 11, characterized in that, The size of the sensing target is determined based on the outline of the sensing target, or it is a preset size.

13. The method according to any one of claims 1 to 12, characterized in that, The method further includes: Send second information to the second sensing node, the second information being used to determine the deviation of the second sensing result, the second sensing result being included in the at least one sensing result.

14. The method according to claim 13, characterized in that, The deviation of the second perception result is the deviation between the position of the perceived target corresponding to the second perception result and the reference position.

15. The method according to any one of claims 1 to 14, characterized in that, The method further includes: Perform point cloud fusion based on the second value.

16. A sensing method, characterized in that, The method includes: Send a first perception result, the first perception result including a first value, the first value being the value of a first parameter; Receive first information, which is used to determine the deviation of the first perception result; Send a second value, which is determined based on the first information and the first value.

17. The method according to claim 16, characterized in that, The first perception result and the second value correspond to the same perception target.

18. The method according to claim 16 or 17, characterized in that, The first perception result is point cloud information.

19. The method according to any one of claims 16 to 18, characterized in that, The first information is determined based on at least one perception result, which includes the first perception result and the second perception result. The second perception result comes from a second perception node, and the first perception result and the second perception result correspond to the same perception target.

20. The method according to any one of claims 16 to 19, characterized in that, The first parameter includes one or more of the following: error covariance parameter, signal-to-noise ratio, error elliptic parameter, error variance parameter, or received signal strength.

21. The method according to any one of claims 16 to 20, characterized in that, The deviation of the first perception result is the deviation between the position of the perceived target corresponding to the first perception result and the reference position.

22. The method according to any one of claims 16 to 21, characterized in that, The first information is used to indicate the deviation; or, The first information is used to indicate the outline of the perceived target; or, The first information is used to indicate the size of the perceived target and the direction of movement of the perceived target.

23. The method according to any one of claims 16 to 22, characterized in that, The first parameter includes the error covariance parameter, and the method further includes: A second distance is determined based on the deviation and the first distance, and a second angle is determined based on the deviation and the first angle, wherein the first distance is the distance between the detected sensing target and the first sensing node, and the first angle is the angle between the detected sensing target and the first sensing node; The second value is determined based on the second distance and the second angle.

24. An apparatus, characterized in that, The apparatus includes a module for performing the method as described in any one of claims 1 to 15, or a module for performing the method as described in any one of claims 16 to 23.

25. An apparatus, characterized in that, The apparatus includes a processor for performing the method as claimed in any one of claims 1 to 15, or for performing the method as claimed in any one of claims 16 to 23.

26. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program that, when run on a computer, causes the method as described in any one of claims 1 to 15 to be performed, or causes the method as described in any one of claims 16 to 23 to be performed.

27. A computer program product, characterized in that, The computer program product includes a computer program that, when run on a computer, causes the computer to perform the method as described in any one of claims 1 to 15, or causes the computer to perform the method as described in any one of claims 16 to 23.

28. A sensing system, characterized in that, The sensing system includes a fusion center and a first sensing node, wherein... The fusion center is used to perform the method as described in any one of claims 1 to 15; The first sensing node is used to perform the method as described in any one of claims 16 to 23.

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