A perception method and apparatus

Abstract

A sensing method and device. A sensing network element determines a first mode according to a first trajectory, the first mode being a determination mode of a threshold value used to detect whether a sensing target exists in an environment, wherein the first mode is a mode related to or unrelated to a prediction result, the prediction result being distribution characteristic information of a first sensing target predicted, and the first trajectory being a moving trajectory of the first sensing target. The sensing network element sends first information, the first information indicating the first mode or the threshold value. Embodiments of the present application can select a suitable mode to determine a threshold value according to a first trajectory, so that the threshold value is more accurate, thereby improving sensing accuracy.

Description

Technical Field

[0001] This application relates to the field of sensing technology, and in particular to a sensing method and apparatus. Background Technology

[0002] Sensing refers to the detection of parameters of targets in the physical environment, such as their location and velocity. It can also be called detection. When performing sensing, a sensing node (such as an access network device or user equipment (UE)) compares the parameters corresponding to the detected sensing information (e.g., power information) with a corresponding threshold to determine whether a target is detected. However, determining this threshold is a problem that urgently needs to be solved. Summary of the Invention

[0003] This application provides a sensing method and apparatus for reasonably determining a threshold. The sensing method and apparatus can also be considered a communication method and apparatus, or an integrated sensing and communication method and apparatus.

[0004] In a first aspect, a first sensing method is provided, which can be applied to a first device. The first device is, for example, a sensing network element, a functional module included in a sensing network element, or a larger device including a sensing network element. 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 the chip system or functional module is, for example, disposed within the network equipment. The network equipment includes, for example, core network equipment and / or access network equipment. 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 such as SF or LMF capable of implementing sensing functions. The method includes: determining a first mode based on a first trajectory, wherein the first mode is a threshold determination mode, the threshold being used to detect whether a sensing target exists in the environment, wherein the first mode is a mode related to or unrelated to a prediction result, the prediction result being the predicted distribution characteristic information of the first sensing target, and the first trajectory being the movement trajectory of the first sensing target; and sending first information, wherein the first information indicates the first mode or the threshold.

[0005] This application embodiment can determine a threshold based on the movement trajectory (first trajectory) of the first perceived target, or determine a method for determining the threshold based on the first trajectory. One method for determining the threshold is related to the prediction result, whereby the first trajectory can reflect, for example, the credibility or reliability of the prediction result. For instance, if the prediction result is credible or reliable, the first method can be related to the prediction result; conversely, if the prediction result is uncredible or unreliable, the first method can be unrelated to the prediction result. Thus, a suitable method can be selected to determine the threshold, making it more accurate and improving perception precision.

[0006] In one optional implementation, determining a first method based on the first trajectory includes: the length of the first trajectory being greater than or equal to a first value, wherein the first method is a method related to the prediction result; or, the length of the first trajectory being less than the first value, wherein the first method is a method unrelated to the prediction result. The length of the first trajectory can reflect the reliability, accuracy, or usability of the prediction result. For example, if the first trajectory is short, the Kalman filter algorithm used to obtain the prediction result may not have converged yet, and the obtained prediction result may not be accurate enough, reliable enough, or usable. Therefore, a method unrelated to the prediction result can be used to determine the threshold. Conversely, if the first trajectory is long, it indicates that the Kalman filter algorithm may have converged, and the obtained prediction result may be more accurate, reliable, or usable. Therefore, a method related to the prediction result can be used to determine the threshold. It is evident that the method provided in this application embodiment can select a reasonable method to determine the threshold, thereby improving the accuracy of the threshold and thus improving the perception accuracy.

[0007] In an optional implementation, the method further includes: receiving first sensing information, the first sensing information indicating the position and / or velocity of the first sensing target; and determining the first trajectory based on the first sensing information. The sensing network element can determine the first trajectory based on the actually obtained first sensing information, or alternatively, the sensing network element can determine the first trajectory through other means, such as predicting the first trajectory based on prior information, etc., without any specific limitations.

[0008] In an optional implementation, the method further includes: determining the prediction result based on the first sensing information. The sensing network element can also obtain the prediction result based on the first sensing information, thereby making it feasible to determine a threshold in a manner related to the prediction result.

[0009] In one optional implementation, the prediction result includes: the location information of the first sensing target at the next time step; and / or, the probability distribution of the first sensing target at the next time step. This prediction result can include the location distribution of the first sensing target at the next time step, or it can be understood as reflecting the possible locations of the first sensing target at the next time step, essentially providing prior distribution information of the first sensing target, which helps in determining whether the first sensing target exists at a certain location.

[0010] In one optional implementation, the first method is a method related to the prediction result, and the first information further includes the prediction result. If the first method is a method related to the prediction result, and the first information indicates the first method, then the first information may further include the prediction result, so that the sensing node can determine a threshold based on the prediction result.

[0011] In an optional implementation, the method further includes: determining the threshold according to the first method. In this implementation, the sensing network element can determine the threshold, eliminating the need for the sensing node to determine the threshold, which simplifies the implementation of the sensing node.

[0012] In one optional implementation, the first method is a method related to the prediction result, and the threshold includes at least one threshold corresponding to at least one resolution unit to be detected; or, the first method is a method unrelated to the prediction result, and the threshold includes one threshold corresponding to all resolution units to be detected. If the first method is a method related to the prediction result, different resolution units can have their own corresponding thresholds, making the thresholds more consistent with the actual situation of the resolution units. For example, if the prediction result indicates that a resolution unit may have a sensing target, the corresponding threshold can be smaller, thereby enabling a higher probability of determining that a sensing target exists at that resolution unit. Conversely, if the prediction result indicates that a resolution unit may not have a sensing target, the corresponding threshold can be larger, thereby enabling a higher probability of determining that no sensing target exists at that resolution unit. Therefore, by combining the prediction result (e.g., understood as prior information) to set appropriate thresholds for different resolution units, the detection result for the sensing target can be more accurate, thereby improving the sensing accuracy. If the first method is a method unrelated to the prediction result, different resolution units can correspond to a unified threshold, and this method of calculating the threshold is relatively simple.

[0013] In one optional implementation, the first method is a method related to the prediction result, and the first method corresponds to a first formula applied to calculate the threshold; or, the first method is a method unrelated to the prediction result, and the first method corresponds to a second formula applied to calculate the threshold. Alternatively, the first method may not correspond to a formula, but rather to a certain method; and / or, the second method may not correspond to a formula, but rather to a certain method. This application embodiment does not impose any limitations on this.

[0014] Secondly, a second sensing method is provided, which can be applied to a second device. The second device is, for example, a sensing node, a functional module included in a sensing node, or a larger device including a sensing node. The second device is, for example, a terminal-side device or a network-side device. 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 chip, such as a modem chip, also known as a baseband chip, or a SoC chip or SIP chip containing a modem core) or other functional module, which can implement the functions of the terminal equipment, and is, for example, disposed in the terminal equipment. The network-side device is also referred to as a network device. The network device is, for example, an access network device, or other equipment including access network device functions, or a circuit, or a system-on-a-chip (or chip) or other functional module, which can implement the functions of the access network device, and is, for example, disposed in the access network device. The access network device can be a non-ORAN architecture or an ORAN architecture; or, the access network device can be a CU, DU, or RU under an ORAN architecture. The access network device may be located on the ground, or it may be a satellite, or located on a satellite. The method includes: receiving first information, the first information indicating a first mode or threshold, the first mode being a method for determining the threshold, the threshold being used to detect the presence of a sensing target in the environment, wherein the first mode is a mode related to or unrelated to a prediction result, and the prediction result is the predicted distribution characteristic information of a first sensing target; and determining the threshold based on the first information.

[0015] In one alternative implementation, the first method is a method related to the prediction result, and the first information further includes the prediction result.

[0016] In one optional implementation, the prediction result includes: the location information of the first perceived target at the next time step; and / or, the probability distribution of the first perceived target at the next time step.

[0017] In one alternative implementation, the first method is a method related to the prediction result, and the threshold includes at least one threshold corresponding to at least one resolving unit to be detected; or, the first method is a method unrelated to the prediction result, and the threshold includes one threshold corresponding to all resolving units to be detected.

[0018] In one alternative implementation, the first method is a method related to the prediction result, and the first method is applied to a first formula for calculating the threshold; or, the first method is a method unrelated to the prediction result, and the first method is applied to a second formula for calculating the threshold.

[0019] For the technical effects of the second aspect or various alternative implementation methods, please refer to the introduction of the technical effects of the first aspect or corresponding implementation methods.

[0020] 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. 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.

[0021] In one optional implementation, the processing unit is configured to determine a first mode based on a first trajectory, wherein the first mode is a threshold determination mode, the threshold being used to detect whether a sensing target exists in the environment, wherein the first mode is a mode related to or unrelated to the prediction result, the prediction result being the predicted distribution characteristic information of the first sensing target, and the first trajectory being the movement trajectory of the first sensing target; the transceiver unit (or the sending unit) is configured to send first information, the first information indicating the first mode or the threshold.

[0022] 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.

[0023] 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.

[0024] In one optional implementation, the transceiver unit (or the receiving unit) is configured to receive first information, the first information being used to indicate a first mode or a threshold, the first mode being a method for determining the threshold, the threshold being used to detect whether a sensing target exists in the environment, wherein the first mode is a mode related to or unrelated to the prediction result, and the prediction result is the distribution characteristic information of the predicted first sensing target; the processing unit is configured to determine the threshold based on the first information.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] In one possible design, the device may also include the memory.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] In one possible design, the device may also include the memory.

[0033] 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.

[0034] A seventh aspect provides a sensing system including a sensing network element. The sensing network element is used to perform the method described in the first aspect, which is executed by the first device. For example, the sensing network element can be implemented using the device described in the third or fifth aspect.

[0035] Optionally, the sensing system may further include sensing nodes. These sensing nodes are used to perform the method described in the second aspect above, which is executed by the second apparatus. The sensing node is, for example, a terminal device or a network device (e.g., an access network device). For example, the terminal device may be implemented using the apparatus described in the fourth or sixth aspect; the network device may be implemented using the apparatus described in the fourth or fifth aspect.

[0036] 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.

[0037] 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.

[0038] 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

[0039] Figure 1 This is a schematic diagram of a single-station sensing mode;

[0040] Figure 2 This is a schematic diagram of a dual-station sensing mode;

[0041] Figure 3 This is a schematic diagram illustrating an application scenario according to an embodiment of this application;

[0042] Figure 4 A flowchart of a sensing method provided in an embodiment of this application;

[0043] Figure 5 A schematic diagram of an apparatus provided in an embodiment of this application;

[0044] Figure 6 This is a schematic diagram of another device provided in an embodiment of this application. Detailed Implementation

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] In this embodiment of the application, the terminal device is a device with wireless transceiver function, which may 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 above devices. The terminal devices are used to connect people, objects, and machines, 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 (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 terminal devices in indoor commercial scenarios (such as mobile phone screen mirroring, file sharing, and mobile phone to VR glasses). 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.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] In this application embodiment, the device for implementing 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.

[0054] 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. The base station can communicate with the terminal device, or it can communicate with the terminal device through a relay station. The 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.

[0055] In the CU-DU architecture, access network equipment can include centralized units (CU) and distributed units.

[0056] One or more logical network elements, such as distributed unit (DU), control plane (CP), user plane (UP), or radio unit (RU). CU and DU can be separate entities or included in the same network element, such as a baseband unit (BBU). RU can be included in radio frequency equipment or radio frequency units, such as remote radio unit (RRU), active antenna unit (AAU), or remote radio head (RRH).

[0057] 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.

[0058] 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.

[0059] In this application embodiment, the device for implementing the network device function can be a network device itself, or a device capable of supporting the network device in implementing that function, such as a chip system, which can be installed in 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.

[0060] 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.

[0061] 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).

[0062] 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).

[0063] 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.

[0064] 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.

[0065] 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.

[0066] Precision, also known as perception precision, describes the error between the perceived result and the ideal, true result. Taking distance perception as an example, if the distance between the perceived target and the sensing device is obtained as 6 meters (m), while the actual distance between the perceived target and the sensing device is 5 meters, then the perception error is 1 meter, also known as perception precision of 1 meter.

[0067] Resolution, also known as perceptual resolution, describes the minimum ability of a sensor to distinguish two different targets. Taking distance sensing as an example, a distance resolution of 1m should be understood as follows: when the distance between two sensed targets is greater than or equal to 1m, the sensing device can distinguish between two targets; while when the distance between the two sensed targets is less than 1m, the sensing device cannot distinguish between two targets.

[0068] False alarm probability is the probability of detecting the presence of a target when the target is not actually present.

[0069] Constant false alarm rate (CFAR) detection is a technique that provides predictable detection and false alarms in real-world interference environments. Common CFAR detection algorithms include cell-average CFAR detection.

[0070] 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 higher level of user experience. Sensing can also be referred to as detection.

[0071] In sensing, based on the different sender and receiver of the sensing signal, sensing modes can be divided into two types: single-station sensing and dual-station sensing. Single-station sensing mode, also known as self-transmitting and self-receiving mode, refers to a mode where the device sending the sensing signal and the device receiving the echo signal reflected from the target are the same device, such as... Figure 1 As shown, both the device transmitting the sensing signal and the device receiving the echo signal are device 1; the dual-station sensing mode, also known as A-transmit B-receive mode or self-transmit and other-receive mode, refers to a mode where the device transmitting the sensing signal and the device receiving the echo signal reflected from the target are different devices, such as... Figure 2 As shown, the device that sends the sensing signal is device 2, and the device that receives the echo signal is device 3. Figure 1 and Figure 2 All examples assume the target (or scatterer) is a vehicle. Typical single-site sensing scenarios include sensing modes where the base station transmits and receives data independently, and sensing modes where the UE transmits and receives data independently. Typical dual-site sensing scenarios include sensing modes where base station A transmits and base station B receives data, sensing modes where the base station transmits and the UE receives data, and sensing modes where the UE transmits and the base station receives data.

[0072] When performing sensing operations, a sensing node (such as an access network device or user equipment (UE)) can detect the presence of a sensing target based on sensing information. For example, the sensing node can use a constant false alarm rate (CFAR) detection method. In CFAR, the sensing node compares the parameters (such as power information) corresponding to the detected sensing information with a corresponding threshold to determine whether a sensing target exists. For instance, the sensing node can determine an imaging frame based on the sensing information. This imaging frame corresponds to an imaging spectrum, which may include multiple resolution cells. For any resolution cell A, at least one resolution cell surrounding resolution cell A can be a reference cell for resolution cell A. The sensing node can determine the power of resolution cell A and the average power of each reference cell corresponding to resolution cell A based on the sensing information. The sensing node calculates the ratio of the power of resolution cell A to the average power. If this ratio is less than a certain threshold, it is considered that no sensing target exists at resolution cell A; if the ratio is greater than the threshold, it is considered that a sensing target exists at resolution cell A. However, how to determine this threshold is currently undetermined.

[0073] Therefore, embodiments of this application propose that a threshold can be determined based on the movement trajectory (first trajectory) of the first perceived target. One method for determining the threshold is a method related to the prediction result, whereby the first trajectory, for example, reflects the credibility or reliability of the prediction result. For instance, if the prediction result is credible or reliable, the first method can be a method related to the prediction result; conversely, if the prediction result is unreliable or untrustworthy, the first method can be a method unrelated to the prediction result. Thus, a suitable method can be selected to determine the threshold, making it more accurate and improving perception precision.

[0074] 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.

[0075] Please refer to Figure 3 This is a schematic diagram of a scenario where communication and sensing are integrated. Figure 3 This includes network equipment and multiple UEs. For example, UE1 and the network equipment adopt a dual-site sensing mode, where UE1 is the transmitter of the sensing signal (or, fusion sensing signal), and the network equipment is the receiver of the echo signal of the sensing signal (or, fusion sensing signal). UE3 and the network equipment also adopt a dual-site sensing mode, where the network equipment 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 equipment and UE2 communicate and can transmit communication signals. Figure 3 It also includes a single-site sensing mode, where the network device senses scatterer 3 and scatterer 5 in a single-site sensing mode. Additionally... Figure 3 In this process, 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.

[0076] Figure 3 Taking UE3 as a vehicle and scatterer 3 as a human body as an example, there are no restrictions on the type of other UEs and scatterers. Figure 3 Take one network device as an example; there may actually be many more network devices.

[0077] 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 signal used for communication is referred to as a communication signal, the signal used for both communication and sensing is referred to as a fusion signal, and the signal used for sensing is referred to as a sensing signal. Both the communication signal and the fusion signal can carry information for communication, such as data and / or control information originating from higher layers. In various embodiments of this application, the signal used for sensing includes, for example, a sensing signal and / or a fusion signal. In various embodiments of this application, the time unit is, for example, a radio frame, a subframe, a slot, a mini-slot, a time-domain symbol group, or a time-domain symbol. In various embodiments of this application, "resolution unit" can also be replaced with "imaging unit," etc., and the name is not limited. In various embodiments of this application, "imaging frame" can also be replaced with "resolution frame" or "sensing frame," etc., and the name is not limited. In the accompanying drawings corresponding to the various embodiments of this application, all steps indicated by dashed lines are optional steps.

[0078] In the 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 functional entity, or a sensing functional network element, etc., and "sensing network element" will be used as an example below. In the various embodiments of this document, a sensing network element can also be called a sensing service function, etc., and there is no limitation on the name. Optionally, a sensing network element can be used to realize the sensing of a sensing target, such as determining the location of the sensing target or reconstructing the environment of the sensing target, etc., without limitation. The embodiments of this application do not limit the deployment of sensing network elements. For example, a sensing network element can be deployed in the core network or in the access network, without limitation. For example, a sensing network element can also be a network management platform or a network management device, etc. It should be understood that in future communication systems, the functional entity used to sense the sensing target can still be called a sensing network element, or it can have other names, and the embodiments of this application do not limit this.

[0079] The various embodiments described herein can be applied to Figures 1-3 The network architecture is shown in any of the accompanying figures. For example, the sensing node described in the various embodiments of this document can be... Figure 1 Device 1 in the document; or, the sensing node described in the various embodiments herein may be... Figure 2Device 3 in the document; or, the sensing node described in the various embodiments herein may be... Figure 3 The sensing node can be a network device or any UE. In the various embodiments described herein, the sensing node is, for example, an access network device or a UE.

[0080] The following describes a sensing method provided by an embodiment of this application. Please refer to [link / reference]. Figure 4 Here is a flowchart of the method.

[0081] S401, The sensing network element determines the first mode based on the first trajectory.

[0082] The first approach can be a threshold determination or calculation method. This first approach can be used to determine or calculate the threshold, which can then be used to determine, detect, or judge the presence of a sensing target in the environment. For example, when performing sensing, a sensing node can detect the presence of a sensing target based on sensing information; for instance, the sensing node can use CFAR detection. The sensing node can determine an imaging frame based on the sensing information. This imaging frame corresponds to an imaging spectrum, which may include multiple resolution cells. For any resolution cell A, at least one resolution cell surrounding resolution cell A can be a protection cell of resolution cell A. Additionally, at least one resolution cell surrounding resolution cell A can be a reference cell of resolution cell A. Optionally, the distance between the reference cell and resolution cell A can be greater than the distance between the protection cell and resolution cell A. In CFAR mode, the sensing node can determine the power of resolution cell A and the average power of each reference cell corresponding to resolution cell A based on the sensing information. The sensing node calculates the ratio of the power of resolution cell A to the average power and can compare this ratio with the threshold. If the ratio is less than the threshold, it is considered that there is no target to be perceived at the resolution unit A; if the ratio is greater than the threshold, it is considered that there is a target to be perceived at the resolution unit A.

[0083] Optionally, S401 can also be replaced with: the sensing element determines a formula based on the first trajectory, which is used to calculate the threshold. Alternatively, S401 can be replaced with: the sensing element determines the method for determining the threshold based on the first trajectory, i.e., "first method" can be replaced with "method for determining the threshold". Alternatively, S401 can be replaced with: the sensing element determines the calculation method for the threshold based on the first trajectory, i.e., "first method" can be replaced with "method for calculating the threshold". Alternatively, S401 can be replaced with: the sensing element determines the formula for determining the threshold based on the first trajectory, i.e., "first method" can be replaced with "formula for determining the threshold". Alternatively, S401 can be replaced with: the sensing element determines the calculation formula for the threshold based on the first trajectory, i.e., "first method" can be replaced with "formula for calculating the threshold". In essence, in S401, the sensing element determines how to calculate the threshold based on the first trajectory.

[0084] The first trajectory can be the movement trajectory of the first sensed target. Optionally, before S401, the method may further include S402, whereby the sensing element determines the first trajectory. For example, one optional way for the sensing element to determine the first trajectory is that the sensing element can determine the first trajectory based on first sensing information. The first sensing information can indicate parameters of the first sensed target, such as the position and / or velocity of the first sensed target, so that the sensing element can determine the first trajectory based on the parameters of the first sensed target. Optionally, the first sensing information can indicate the position of the first sensed target by including position information of the first sensed target, such as the coordinates of the first sensed target in a Cartesian coordinate system, or one or more of the distance, azimuth, or pitch angle of the first sensed target in a polar coordinate system, or the position information may have other implementations. Optionally, the first sensed target indicates the velocity of the first sensed target, such as including the radial velocity of the first sensed target.

[0085] Optionally, the first sensing information can come from the sensing node. For example, the sensing node performs sensing and obtains the first sensing information; the sensing node sends the first sensing information to the sensing network element, then the sensing network element can obtain the first sensing information.

[0086] The sensing element receives first sensing information and can determine the movement trajectory of the first sensing target based on this information. Optionally, the sensing element can determine only the movement trajectory of the first sensing target based on the first sensing information; or, the sensing element can determine the movement trajectories of multiple sensing targets based on the first sensing information, with the first sensing target being one of these multiple sensing targets. For example, the first sensing information may include information from an imaging frame corresponding to the first sensing target; or, the first sensing information may include information from multiple imaging frames corresponding to multiple sensing targets, such as a one-to-one correspondence between imaging frames and sensing targets, where the multiple sensing targets include the first sensing target.

[0087] For example, the imaging frame corresponding to the first perceived target can correspond to an imaging spectrum, which includes multiple resolution units (e.g., the imaging spectrum includes multiple pixels, each of which can be called a resolution unit). The perception network element can perform point cloud clustering on the imaging spectrum to determine a location corresponding to the first perceived target. For example, multiple resolution units within the imaging spectrum may contain information related to the first perceived target. In this case, the perception network element can aggregate these multiple resolution units by performing point cloud clustering on the imaging spectrum to determine a location corresponding to the first perceived target.

[0088] In addition to point cloud clustering, the sensing network element can optionally perform track association to obtain a first trajectory. For example, before receiving the first sensing information, the sensing network element may have received at least one other sensing information from the sensing node. The sensing network element also performs point cloud clustering on each imaging spectrum corresponding to the at least one sensing information. For example, the sensing network element can determine M positions corresponding to the first sensing target based on the imaging spectrum corresponding to the at least one sensing information, where M is a positive integer. By integrating some or all of the sensing information obtained, the sensing network element can perform track association on the positions corresponding to the same sensing target (e.g., the first sensing target) to obtain the movement trajectory of the first sensing target, i.e., the first trajectory. For example, before determining the first trajectory, the sensing network element may have already determined the movement trajectory of the first sensing target based on the at least one sensing information, which may be called the second trajectory, and the second trajectory includes M positions of the first sensing target. If the sensing network element then determines one position of the first sensing target based on the first sensing information, it can add that position to the second trajectory to obtain the first trajectory, which includes M+1 positions of the first sensing target. If the sensing element continues to receive sensing information from the sensing nodes, it can continue to associate the position of the first sensing element with the first trajectory. If there are multiple sensing targets, the processing method for each sensing target by the sensing element can be similar.

[0089] The sensing element obtains a first trajectory and can determine a first method based on the first trajectory. Optionally, if the length of the first trajectory is greater than or equal to a first value, the first method can be a method related to the prediction result; or, if the length of the first trajectory is less than the first value, the first method can be a method unrelated to the prediction result.

[0090] The prediction result is the predicted distribution characteristic information of the first sensed target, which can indicate the positional distribution characteristics of the first sensed target. Optionally, the prediction result may include the positional information of the first sensed target at the next time step, and / or include the distribution probability of the first sensed target at the next time step (e.g., positional distribution probability). Both the positional information and the distribution probability can be predicted information, determined based on prediction. For example, the prediction result may include a first mean and / or a covariance matrix. The first mean represents the mean of the positional distribution of the first sensed target, which can characterize the predicted positional information of the first sensed target at the next time step. The covariance matrix can characterize the predicted distribution probability of the first sensed target at the next time step.

[0091] The next moment can be, for example, the time corresponding to the next imaging frame, such as the time when the next imaging frame is obtained, or the time when the next imaging frame is processed. Alternatively, the next moment can be, for example, the next time unit. Alternatively, the next moment can be, for example, the time corresponding to the frame number of the next imaging frame, such as the time when the frame number of the next imaging frame is started. Alternatively, the next moment can also be any time after the current moment.

[0092] Optionally, the prediction result can be determined by the sensing network element based on the first sensing information; that is, the sensing network element can determine the first trajectory and the prediction result based on the first information. For example, the sensing network element can perform Kalman filtering on the first sensing information to obtain the prediction result. Alternatively, the sensing network element can obtain the prediction result through other methods, without limitation.

[0093] The length of the first trajectory can reflect the reliability, accuracy, or usability of the prediction result. For example, if the first trajectory is short, the Kalman filter algorithm may not have converged yet, and the resulting prediction may be inaccurate, unreliable, or unusable. Therefore, if the length of the first trajectory is less than a first value (or less than or equal to the first value), the threshold can be determined in a way unrelated to the prediction result. Conversely, if the first trajectory is long, it indicates that the Kalman filter algorithm may have converged, and the resulting prediction may be more accurate, reliable, or usable. Therefore, if the length of the first trajectory is greater than or equal to the first value (or greater than the first value), the threshold can be determined in a way related to the prediction result. It is evident that the method provided in this application can select a reasonable way to determine the threshold, improving the accuracy of the threshold and thus enhancing the perception precision.

[0094] Optionally, if the first method is related to the prediction result, then the first method can correspond to the first formula or the first method is the first formula, and the first formula is used to calculate the threshold; or, if the first method is unrelated to the prediction result, then the first method can correspond to the second formula or the first method is the second formula, and the second formula is used to calculate the threshold.

[0095] Taking the first method corresponding to the first formula, or the first method being the first formula, as an example, the first method is related to the prediction result. For example, it can be implemented as follows: The first formula includes the prediction result. For example, the first formula is as follows:

[0096]

[0097] in, ρ represents the l-th resolution cell in the k-th imaging frame. k η represents the average signal-to-noise ratio of the k-th imaging frame. η represents the false alarm rate.

[0098] γ BD This represents the calculated threshold. BD represents Bayes' theorem. ln(x) represents the natural logarithm. Indicates The mean is D k|k-1 Let be the probability at the l-th resolution cell in the k-th frame, representing the Gaussian distribution of the covariance matrix. This represents the predicted location information of the l-th resolution unit in the k-th frame. Wherein, It can be obtained from the prediction results, for example D can be obtained from the prediction results, including the position information of the first perceived target at the next moment. k|k-1 It can be obtained from the distribution probability of the first perceived target in the next moment, which is included in the prediction result. Therefore, it is believed that the first formula or the first method is related to the prediction result. This represents the average false alarm rate under Bayes' theorem. H1 indicates the presence of a target. H0 indicates the absence of a target.

[0099] Taking the first method corresponding to the second formula, or the first method being the second formula, as an example, the first method is unrelated to the prediction result; for example, it is implemented as follows: the second formula does not include the prediction result. For example, the second formula is as follows:

[0100]

[0101] in, ρ represents the l-th resolving unit of the k-th imaging frame, and NP represents the Neyman-Pearson criterion. k γ represents the average signal-to-noise ratio of the k-th imaging frame. η represents the false alarm rate. NP Let represent the calculated threshold. ln(x) represents the natural logarithm. H1 indicates the presence of the target. H0 indicates the absence of the target. It can be seen that the second formula does not include the prediction result; therefore, the second formula or the second method is considered irrelevant to the prediction result.

[0102] S403. The sensing network element sends the first information to the sensing node. Correspondingly, the sensing node receives the first information.

[0103] The first information can indicate a first method or a threshold. The threshold can be a threshold determined by the sensing network element based on the first method.

[0104] The sensing network element can indicate a first method to the sensing node, which then calculates the threshold based on the first method. The sensing network element does not need to perform the threshold calculation itself, simplifying its implementation. If the first information indicates the first method, and the first method is related to the prediction result, then optionally, the first information may also include the prediction result, allowing the sensing node to calculate the threshold accordingly.

[0105] Alternatively, the sensing element can calculate the threshold according to the first method, and then instruct the sensing node to set the threshold according to the first information. The sensing node does not need to calculate the threshold, but can determine the first threshold according to the first information. This makes the embodiments of this application applicable to sensing nodes with lower capabilities, which is beneficial to expanding the scope of application of the embodiments of this application.

[0106] Optionally, if the first method is unrelated to the prediction result, the number of thresholds obtained based on the first method can be 1. That is, a threshold can be obtained based on the first method, and this threshold can be applied to all resolving units to be detected. For example, regardless of which resolving unit the sensing node needs to determine whether a sensing target exists, it can make the determination based on this threshold.

[0107] Alternatively, if the first method is related to the prediction result, the number of thresholds obtained according to the first method can be greater than or equal to 1. That is, at least one threshold can be obtained according to the first method, and this at least one threshold can be applied to at least one resolution unit to be detected. For example, the at least one threshold can correspond one-to-one with the at least one resolution unit; or, one of the at least one thresholds can correspond to one or more resolution units. The at least one resolution unit can be all or some of the resolution units to be detected. For example, if a sensing node wants to determine whether a sensing target exists in resolution unit A, it can make the determination based on the threshold corresponding to resolution unit A; if a sensing node wants to determine whether a sensing target exists in resolution unit B, it can make the determination based on the threshold corresponding to resolution unit B, and so on. The thresholds corresponding to different resolution units can be equal or unequal.

[0108] The sensing node obtains a threshold based on the first information, and can then detect whether a sensing target exists in the corresponding resolution unit based on this threshold. Specific detection methods can be found in the preceding descriptions. If the first method is related to the prediction result, different resolution units can use different thresholds. For example, if the prediction result indicates that a sensing target may exist in a resolution unit, the corresponding threshold can be smaller, thus allowing for a higher probability of determining that a sensing target exists at that resolution unit. Conversely, if the prediction result indicates that a sensing target may not exist in a resolution unit, the corresponding threshold can be larger, thus allowing for a higher probability of determining that a sensing target does not exist at that resolution unit. Therefore, by combining the prediction result (e.g., understood as prior information) with setting appropriate thresholds for different resolution units, the detection results for sensing targets can be more accurate, thereby improving sensing precision.

[0109] Based on detection, the sensing node can obtain sensing information, such as second sensing information. Optionally, the sensing node can send the second sensing information to the sensing network element, as shown in S404. The second sensing information can indicate parameters of the first sensing target, such as the position and / or velocity of the first sensing target. For example, the sensing network element can further refine the first trajectory based on the parameters of the first sensing target, etc., which will not be elaborated further.

[0110] In summary, embodiments of this application can determine a threshold based on the movement trajectory (first trajectory) of the first perceived target. One method for determining the threshold is a method related to the prediction result, whereby the first trajectory, for example, reflects the credibility or reliability of the prediction result. For instance, if the prediction result is credible or reliable, the first method can be a method related to the prediction result; conversely, if the prediction result is unreliable or untrustworthy, the first method can be a method unrelated to the prediction result. Thus, a suitable method can be selected to determine the threshold, making it more accurate and improving perception precision.

[0111] Figure 5 A schematic diagram of a device provided in an embodiment of this application is given. The device 500 may be... Figure 4 The sensing network element or its circuit system described in the illustrated embodiment is used to implement the method corresponding to the sensing network element in the above method embodiments. Alternatively, the device 500 may be... Figure 4 The sensing node or its circuit system described in the illustrated embodiment is used to implement the method corresponding to the sensing node in the above method embodiments. For example, one type of circuit system is a chip system.

[0112] Since the device 500 in the embodiments of this application can implement the sensing method, the device 500 can also be called a sensing device. In implementation, the device 500 may have sensing function but no communication function, or it may have both sensing and communication functions. If the device 500 has communication function, it may also be called a communication device, etc., without limitation.

[0113] The device 500 includes at least one processor 501. The processor 501 can be used for internal processing within the device to implement certain control processing functions. Optionally, the processor 501 includes instructions. Optionally, the processor 501 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 on one or more integrated circuits.

[0114] Optionally, the device 500 includes one or more memories 503 for storing instructions. Optionally, the memories 503 may also store data. The processor and the memories may be separate or integrated together.

[0115] Optionally, the device 500 includes a communication line 502 and at least one communication interface 504. Since the memory 503, communication line 502, and communication interface 504 are all optional, therefore... Figure 5 All are represented by dashed lines.

[0116] Optionally, device 500 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 realize the transmission and reception functions of device 500 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.

[0117] Processor 501 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.

[0118] Communication line 502 may include a path for transmitting information between the aforementioned components.

[0119] Communication interface 504 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.

[0120] Memory 503 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. Memory 503 may exist independently and be connected to processor 501 via communication line 502. Alternatively, memory 503 may be integrated with processor 501.

[0121] The memory 503 stores computer execution instructions for implementing the scheme of this application, and its execution is controlled by the processor 501. The processor 501 executes the computer execution instructions stored in the memory 503, thereby realizing... Figure 4 The steps performed by the sensing network element or sensing node in the illustrated embodiment.

[0122] 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.

[0123] In a specific implementation, as one example, the processor 501 may include one or more CPUs, for example... Figure 5 CPU0 and CPU1 in the CPU.

[0124] In a specific implementation, as one embodiment, device 500 may include multiple processors, for example... Figure 5 Processors 501 and 505 are described in the text. Each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, "processor" can refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0125] when Figure 5When the device shown is a chip, such as a chip for a sensing network element or a sensing node, the chip includes a processor 501 (and may also include a processor 505), a communication line 502, and a communication interface 504. Optionally, it may include a memory 503. Specifically, the communication interface 504 may be an input interface, pins, or circuits, etc. The memory 503 may be a register, cache, etc. The processor 501 and processor 505 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.

[0126] This application embodiment can divide the device into functional modules according to the above method example. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware or as software functional modules. The module division in this application embodiment is illustrative and only represents one logical functional division; in actual implementation, other division methods may be used. For example, in the case of dividing the device into functional modules corresponding to each function... Figure 6 This is a schematic diagram of an apparatus. The apparatus 600 can be a sensing network element or sensing node involved in the above-described method embodiments, or a chip in a sensing network element or a chip in a sensing node. The apparatus 600 includes a processing unit 602 and a transceiver unit 601. Since the apparatus 600 in the embodiments of this application can implement a sensing method, the apparatus 600 can also be called a sensing device. In implementation, the apparatus 600 may have sensing functionality but no communication functionality, or it may have both sensing and communication functionality. If the apparatus 600 has communication functionality, it can also be called a communication device, etc., without limitation.

[0127] It should be understood that the device 600 can be used to implement the steps performed by sensing network elements or sensing nodes in the sensing method of the embodiments of this application, and the relevant features can be referred to above. Figure 4 The embodiments shown are not described in detail here.

[0128] Optional, Figure 6 The functions / implementation process of the transceiver unit 601 and the processing unit 602 can be obtained through Figure 5 The processor 501 in the memory calls computer execution instructions stored in memory 503 to implement the function. Alternatively, Figure 6 The function / implementation process of the processing unit 602 can be achieved through... Figure 5 The processor 501 in the memory calls computer execution instructions stored in the memory 503 to implement this. Figure 6 The function / implementation process of the transceiver unit 601 can be obtained through Figure 5 It is implemented using the communication interface 504.

[0129] Optionally, when the device 600 is a chip or circuit, the function / implementation process of the transceiver unit 601 can also be implemented through pins or circuits. Optionally, the transceiver unit 601 may include a transmitting unit and / or a receiving unit, whereby the transmitting unit implements the transmitting function and the receiving unit implements the receiving function; or, the transceiver unit 601 may be an integral module capable of implementing both transmitting and / or receiving functions. Optionally, the transceiver unit 601 can be implemented using a transceiver.

[0130] This application also provides a computer-readable storage medium storing a computer program or instructions that, when executed, implement the methods performed by the sensing network elements and / or sensing nodes 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.

[0131] 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 sensing network element and / or sensing node in any of the foregoing method embodiments.

[0132] This application also provides a processing device, including a processor and an interface; the processor is used to execute the methods performed by the sensing network elements and / or sensing nodes involved in any of the above method embodiments.

[0133] 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)).

[0134] 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.

[0135] 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.

[0136] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0137] 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.

[0138] It is understood that in the embodiments of this application, the sensing network elements and / or sensing nodes 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 sensing method, characterized in that, The method includes: A first method is determined based on a first trajectory. The first method is a method for determining a threshold. The threshold is used to detect whether a sensing target exists in the environment. The first method is a method that is related to or unrelated to the prediction result. The prediction result is the distribution feature information of the first sensing target obtained from the prediction. The first trajectory is the movement trajectory of the first sensing target. Send a first message, which indicates the first method or the threshold.

2. The method according to claim 1, characterized in that, Determining the first method based on the first trajectory includes: The length of the first trajectory is greater than or equal to a first value, and the first method is a method related to the prediction result; or, The length of the first trajectory is less than a first value, and the first method is a method unrelated to the prediction result.

3. The method according to claim 1 or 2, characterized in that, The method further includes: Receive first sensing information, the first sensing information being used to indicate the position and / or velocity of the first sensing target; The first trajectory is determined based on the first sensed information.

4. The method according to claim 3, characterized in that, The method further includes: The prediction result is determined based on the first perceived information.

5. The method according to any one of claims 1 to 4, characterized in that, The prediction results include: The location information of the first sensed target at the next moment; and / or, The probability distribution of the first perceived target at the next moment.

6. The method according to any one of claims 1 to 5, characterized in that, The first method is a method related to the prediction result, and the first information also includes the prediction result.

7. The method according to any one of claims 1 to 5, characterized in that, The method further includes: The threshold is determined according to the first method.

8. The method according to any one of claims 1 to 7, characterized in that, The first method is a method related to the prediction result, wherein the threshold includes at least one threshold, and the at least one threshold corresponds to at least one resolving unit to be detected; or, The first method is a method unrelated to the prediction result, and the threshold includes a threshold that corresponds to all the resolving units to be detected.

9. The method according to any one of claims 1 to 8, characterized in that, The first method is a method related to the prediction result, and the first method is applied to a first formula for calculating the threshold; or, The first method is a method unrelated to the prediction result, and the first method is applied to the second formula used to calculate the threshold.

10. A sensing method, characterized in that, The method includes: Receive first information, the first information is used to indicate a first method or a threshold, the first method is a method for determining the threshold, the threshold is used to detect whether there is a sensing target in the environment, wherein the first method is a method related to or unrelated to the prediction result, and the prediction result is the distribution feature information of the predicted first sensing target; The threshold is determined based on the first information.

11. The method according to claim 10, characterized in that, The first method is a method related to the prediction result, and the first information also includes the prediction result.

12. The method according to claim 10 or 11, characterized in that, The prediction results include: The location information of the first sensed target at the next moment; and / or, The probability distribution of the first perceived target at the next moment.

13. The method according to any one of claims 10 to 12, characterized in that, The first method is a method related to the prediction result, wherein the threshold includes at least one threshold, and the at least one threshold corresponds to at least one resolving unit to be detected; or, The first method is a method unrelated to the prediction result, and the threshold includes a threshold that corresponds to all the resolving units to be detected.

14. The method according to any one of claims 10 to 13, characterized in that, The first method is a method related to the prediction result, and the first method is applied to a first formula for calculating the threshold; or, The first method is a method unrelated to the prediction result, and the first method is applied to the second formula used to calculate the threshold.

15. A sensing method, characterized in that, The method includes: The sensing network element determines a first method based on a first trajectory. The first method is a threshold determination method, and the threshold is used to detect whether a sensing target exists in the environment. The first method is a method that is related to or unrelated to the prediction result. The prediction result is the predicted distribution feature information of the first sensing target, and the first trajectory is the movement trajectory of the first sensing target. The sensing network element sends first information to the sensing node, the first information indicating the first method or the threshold. The sensing node receives the first information; The sensing node determines the threshold based on the first information.

16. The method according to claim 15, characterized in that, The sensing node is an access network device or terminal.

17. An apparatus, characterized in that, The apparatus includes a module for performing the method as described in any one of claims 1 to 9, or a module for performing the method as described in any one of claims 10 to 14.

18. An apparatus, characterized in that, The apparatus includes a processor for performing the method as described in any one of claims 1 to 9, or the method as described in any one of claims 10 to 14.

19. 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 9 to be performed, or causes the method as described in any one of claims 10 to 14 to be performed.

20. 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 9, or causes the computer to perform the method as described in any one of claims 10 to 14.

21. A sensing system, characterized in that, The sensing system includes sensing network elements and sensing nodes, wherein... The sensing network element is used to perform the method as described in any one of claims 1 to 9; The sensing node is used to perform the method as described in any one of claims 10 to 14.

Images