Sensing channel modeling method and apparatus, device, and storage medium

Abstract

A sensing channel modeling method and apparatus, a device, and a storage medium, relating to the technical field of communications. The method is executed by a first device. The method comprises: determining a wireless signal model of a sensing target, the wireless signal model comprising a signal model of at least one wireless sub-path signal, one wireless sub-path signal corresponding to one scattering point of the sensing target, and the scattering point being the position where the sensing target reflects and / or scatters a sensing signal. A wireless signal model of a sensing target is constructed by means of a signal model of at least one wireless sub-path signal, and one wireless sub-path signal corresponds to one scattering point. The signal model of the wireless sub-path signal can simulate micromotion of the sensing target, and micromotion modeling based on the wireless sub-path signal is more consistent with actual conditions of the local motion of the sensing target. By constructing the wireless signal model of the sensing target on the basis of the signal model of the at least one wireless sub-path signal, the wireless signal model finally obtained is more adapted to actual conditions of the sensing target.

Description

Modeling method, device, equipment and storage medium of perceptual channel Technical Field

[0001] The embodiments of the present application relate to the field of communication technology, and in particular to a modeling method, apparatus, device, and storage medium for a perceptual channel. Background Art

[0002] With the development of wireless sensing technology, synaesthesia integration has gradually come into people's attention. Human body monitoring and behavior perception are important application scenarios of synaesthesia integration.

[0003] For human monitoring and behavioral perception, small movements (referred to as micro-motions) require direct time-of-flight measurement, which requires ultra-wideband signals. Therefore, phase-detection-based signal processing techniques are necessary for human monitoring and behavioral perception research. Accordingly, modeling the perception channel needs to incorporate the effect of distance on the phase of the perception channel.

[0004] How to model the perceptual channel requires further discussion and research.

[0005] Summary of the Invention

[0006] The present invention provides a method, apparatus, device, and storage medium for modeling a perceptual channel. The technical solution is as follows:

[0007] According to one aspect of an embodiment of the present application, a method for modeling a perceptual channel is provided, the method being performed by a first device and including:

[0008] Determine a wireless signal model of a perception target, where the wireless signal model includes a signal model of at least one wireless subpath signal, where one wireless subpath signal corresponds to a scattering point of the perception target, and where the scattering point is a location where the perception target reflects and / or scatters a perception signal.

[0009] According to one aspect of an embodiment of the present application, a device for modeling a perceptual channel is provided, the device comprising:

[0010] A processing module is used to determine a wireless signal model of a perception target, where the wireless signal model includes a signal model of at least one wireless subpath signal, where one wireless subpath signal corresponds to a scattering point of the perception target, and the scattering point is a location where the perception target reflects and / or scatters the perception signal.

[0011] According to one aspect of an embodiment of the present application, a device is provided, comprising a processor and a memory, wherein a computer program is stored in the memory, and the processor executes the computer program to implement the above-mentioned perceptual channel modeling method.

[0012] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored. The computer program is configured to be executed by a processor to implement the above-mentioned perceptual channel modeling method.

[0013] According to one aspect of an embodiment of the present application, a chip is provided, which includes a programmable logic circuit and / or program instructions. When the chip is running, it is used to implement the above-mentioned perceptual channel modeling method.

[0014] According to one aspect of an embodiment of the present application, a computer program product is provided, which includes computer instructions stored in a computer-readable storage medium. A processor reads and executes the computer instructions from the computer-readable storage medium to implement the above-mentioned perceptual channel modeling method.

[0015] The technical solutions provided by the embodiments of the present application may have the following beneficial effects:

[0016] A wireless signal model of the perceived target is constructed using the signal model of at least one wireless subpath signal, with each wireless subpath signal corresponding to a scattering point. This signal model can simulate the micro-movements of the perceived target. Micro-movement modeling based on wireless subpath signals better matches the actual local motion of the perceived target. Constructing a wireless signal model of the perceived target based on the signal model of at least one wireless subpath signal ensures that the resulting wireless signal model is more accurately aligned with the actual situation of the perceived target. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] FIG1 is a schematic diagram of a network architecture provided by an embodiment of the present application;

[0018] FIG2 is a flow chart of a method for modeling a perceptual channel provided by one embodiment of the present application;

[0019] FIG3 is a schematic diagram of a sit-up exercise provided by one embodiment of the present application;

[0020] FIG4 is a block diagram of a modeling apparatus for perceptual channels provided by one embodiment of the present application;

[0021] FIG5 is a schematic structural diagram of a device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0023] The network architecture and business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. A person skilled in the art will appreciate that, with the evolution of the network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0024] Please refer to FIG1 , which shows a schematic diagram of a network architecture 100 provided by an embodiment of the present application. The network architecture 100 may include: a terminal device 10 , an access network device 20 , and a core network element 30 .

[0025] The terminal device 10 may refer to a UE (User Equipment), a STA (Station), an access terminal, a user unit, a user station, a mobile station, a mobile station, a remote station, a remote terminal, a mobile device, a wireless communication device, a user agent, or a user apparatus. In some embodiments, the terminal device 10 may also be a cellular phone, a cordless phone, a SIP (Session Initiation Protocol) phone, a WLL (Wireless Local Loop) station, a PDA (Personal Digital Assistant), a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a 5GS (5th Generation System) or a terminal device in a future evolved PLMN (Public Land Mobile Network), etc., and the embodiments of the present application are not limited thereto. For ease of description, the above-mentioned devices are collectively referred to as terminal devices. The number of terminal devices 10 is generally multiple, and one or more terminal devices 10 may be distributed in each cell managed by an access network device 20. The terminal device may also be referred to as a terminal or UE for short, and those skilled in the art may understand its meaning.

[0026] The access network device 20 is a device deployed in the access network to provide wireless communication functions for the terminal device 10. The access network device 20 may include various forms of macro base stations, micro base stations, relay stations, APs (Access Points), etc. In systems using different wireless access technologies, the names of devices with access network device functions may be different. For example, in the 5G NR (New Radio) system, it is called gNodeB or gNB (Next Generation Node B). With the evolution of communication technology, the name "access network device" may change. For the convenience of description, in the embodiments of the present application, the above-mentioned devices that provide wireless communication functions for the terminal device 10 are collectively referred to as access network devices. In some embodiments, a communication relationship can be established between the terminal device 10 and the core network network element 30 through the access network device 20. For example, in an LTE (Long Term Evolution) system, the access network device 20 may be an Evolved Universal Terrestrial Radio Access Network (EUTRAN) or one or more eNodeBs in the EUTRAN. In a 5G NR system, the access network device 20 may be a Radio Access Network (RAN) or one or more gNBs in the RAN. In the embodiments of the present application, unless otherwise specified, the "network device" referred to refers to the access network device 20, such as a base station.

[0027] The core network element 30 is a network element deployed in the core network. The functions of the core network element 30 are mainly to provide user connection, user management, and service bearer, and to provide an interface to the external network as a bearer network. For example, the core network elements in the 5G NR system may include network elements such as the AMF (Access and Mobility Management Function) entity, the UPF (User Plane Function) entity, and the SMF (Session Management Function) entity.

[0028] In some embodiments, the access network device 20 and the core network element 30 communicate with each other via an air interface technology, such as the NG interface in the 5G NR system. The access network device 20 and the terminal device 10 communicate with each other via an air interface technology, such as the Uu interface.

[0029] The "5G NR system" in the embodiments of the present application may also be referred to as a 5G system or an NR system, but those skilled in the art will understand its meaning. The technical solutions described in the embodiments of the present application may be applicable to LTE systems, 5G NR systems, and subsequent evolution systems of 5G NR systems (e.g., B5G (Beyond 5G) systems, 6G systems (6th Generation System, sixth generation mobile communication systems)), and other communication systems such as NB-IoT (Narrow Band Internet of Things) systems, which are not limited in this application.

[0030] In an embodiment of the present application, the network device can provide services for a cell, and the terminal device communicates with the network device through the transmission resources (for example, frequency domain resources, or spectrum resources) on the carrier used by the cell. The cell can be a cell corresponding to the network device (for example, a base station). The cell can belong to a macro base station or a base station corresponding to a small cell. The small cells here may include: metro cell, micro cell, pico cell, femto cell, etc. These small cells have the characteristics of small coverage and low transmission power, and are suitable for providing high-speed data transmission services.

[0031] Before introducing the technical solutions of this application, we first introduce and explain some of the relevant technical knowledge involved in this application. The following related technologies can be combined with the technical solutions of the embodiments of this application as optional solutions, and they all fall within the scope of protection of the embodiments of this application. The embodiments of this application include at least part of the following contents.

[0032] 1. Communication and perception integration

[0033] Next-generation networks (such as 6G networks) are expected to be a fusion of mobile communication networks, perception networks, and computing networks. In a narrow sense, a perception network refers to a system capable of target positioning (ranging, speed, and angle measurement), target imaging, target detection, target tracking, and target recognition. In a broader sense, it refers to a system that understands the attributes and status of all services, networks, users, and terminals, as well as environmental objects. From the perspective of perception applications, perception can be categorized as follows:

[0034] - Outdoor / wide-area / local-area applications: including smart cities (e.g., weather monitoring), smart transportation / high-speed rail (e.g., high-precision map construction, road supervision, intrusion detection), and low-altitude applications (e.g., drone monitoring and obstacle avoidance, flight intrusion detection, flight path management).

[0035] - Indoor / local applications: including smart home and health management (such as respiratory monitoring, intrusion detection, gesture / posture recognition, motion monitoring, mobile trajectory tracking, etc.), smart factories (such as intrusion detection, material detection, object defect detection, etc.), etc.

[0036] The above is just an example, providing some classifications of perception applications. The application scope of perception is not limited to the above examples.

[0037] 2. Micro-motion perception

[0038] Human monitoring and behavioral perception are important application scenarios for synaesthesia integration. For these applications, small movements (micromotions, or micro-movements) are required, relying on direct time-of-flight measurement. This requires ultra-wideband signals. For example, a resolution of 1cm requires a signal bandwidth of 15GHz. Low-frequency and millimeter-wave bands struggle to provide such wide bandwidths. Therefore, phase-detection-based signal processing techniques are necessary for research on human monitoring and behavioral perception. Accordingly, channel modeling needs to account for the effect of distance on phase.

[0039] 3. Micro-motion perception channel modeling

[0040] Theoretically, the amplitude, phase, and delay of the channel parameters are all affected by the propagation distance of the perceived signal. Therefore, in the small-scale channel model, the amplitude, phase, and delay of the channel parameters need to introduce distance variables.

[0041] For channel amplitude, the distance effect is mainly reflected by the large-scale fading model. Usually, the large-scale fading model is a function related to distance and frequency, that is, PL = g(d 3D ,f0). Where PL represents the energy change of the perception signal, and its unit is dBw; d 3D represents the propagation distance of the sensing signal, which is the total distance from the transmitter of the sensing signal to the sensing target, and then reflected by the sensing target to the receiver of the sensing signal; f0 represents the frequency of the sensing signal; g(d 3D ,f0) represents d 3D The functional relationship between and f0 is not limited in this application. For example, the functional relationship can be a free space propagation model, or a free space propagation model modified by adding an occlusion function.

[0042] For channel phase, the distance effect is reflected by the distance-dependent phase term in the small-scale parameter. Formula 1 is the small-scale channel model of the perceptual channel modeled using a segmented approach.

[0043] It should be noted that since the above formula is long, a line break is added after it for its normal display in the document. It should be understood that To solve Then multiply by The result of , wherein x is used to refer to the content after the summation symbol in the above formula 1. For other long formulas in the embodiments of this application, they should also be understood in the same way as the above formula, and this application will not repeat them one by one.

[0044] Where u represents the receiving antenna of the sensing signal, s represents the transmitting antenna of the sensing signal, and M represents the number of wireless subpath signals. The energy change of the perceived signal between the transmitting antenna s and the receiving antenna u. The parameters of the channel from the transmitter of the sensing signal to the sensing target can be calculated by the position of the transmitter of the sensing signal and the sensing target. These are the channel parameters from the sensing target to the receiving end of the sensing signal. These parameters can be calculated through the position of the receiving end of the sensing signal and the sensing target. represents the sending vector of the transmitter of the perception signal, represents the receiving vector of the perceived target, represents the sending vector of the sensing target, represents the receiving vector of the receiving end of the sensing signal. m (t) represents the micro-motion model of the scattering point, d 3D It represents the sum of the distance from the transmitter of the perception signal to the perception target and the distance from the perception target to the receiver of the perception signal. Represents the velocity vector of the perceived target, which has a certain directionality. rx,u,θ and The receiving antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vectors θ and Field strength diagram on the tx,u,θ and The transmitting antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vector θ and Field strength diagram on . represents the horizontal arrival angle of the perceived signal, θ β,m,ZOA represents the vertical angle of arrival of the perceived signal, represents the horizontal departure angle of the perceived signal, θ α,m,ZOD Indicates the vertical departure angle of the perceived target, represents the location of the receiving antenna that senses the signal, represents the location of the transmitting antenna of the sensing signal, represents the cross-polarization power ratio, λ0 represents the wavelength of the perceived signal, Indicates the phase change of the perceived signal.

[0045] in, It reflects the impact of static distance or initial distance on channel phase.

[0046] Currently, the channel model has taken into account the impact of the initial distance on the phase. However, the impact of motion on the channel only uses the simple assumption of uniform linear motion. Such an assumption cannot meet the perception requirements of perception applications, especially micro-motion patterns. Taking respiratory monitoring as an example, the perception requirement is not to obtain the movement speed of the chest during breathing, but to obtain the frequency of chest heaves. The two are not equivalent, that is, the frequency of chest heaves cannot be inferred from the movement speed of the chest. Specifically, when the movement speed of the chest is known, but the amplitude information of the chest movement is missing, it is still impossible to calculate the time of one chest heave, and accordingly, the frequency of chest heaves cannot be obtained. If it is assumed that the amplitude of the chest movement is fixed (this assumption is not entirely reasonable), but due to different perception angles, the projection length of the amplitude of the chest movement in the direction of the perception signal is still unknown. Therefore, in micro-motion modeling, especially when the perception requirement is not speed, but motion pattern or regularity, the speed-related phase term needs to adopt an accurate motion model, that is will be Instead, where f(t) is the relative motion model between the sensing target and the sensing node. Accordingly, Formula 1 needs to be modified as follows:

[0047] The parameters in the above formula have the same meanings as those in Formula 1. Please refer to the parameter interpretations in Formula 1 and this application will not repeat them here.

[0048] However, using the human breathing model as an example, the f(t) in the above method only represents the breathing state. If the person being sensed is walking, this method cannot describe their walking state. The overall movement of the sensed target is not modeled, and all scattering points of the sensed target use the same micro-motion model, which is inconsistent with reality. Scattering points refer to different points on the sensed target, or the different locations on the sensed target that reflect or scatter the sensing signal.

[0049] The embodiment of the present application provides a modeling method for a perception channel, which can simulate both the moving speed and the micro-motion of the perception target, and performs micro-motion modeling based on the wireless sub-path signals corresponding to each scattering point, which is more consistent with the actual situation of local movement.

[0050] Please refer to FIG2 , which shows a flow chart of a method for modeling a perceptual channel according to an embodiment of the present application. The method is executed by a first device and includes the following step 210 .

[0051] In step 210, the first device determines a wireless signal model of the sensing target. The wireless signal model includes a signal model of at least one wireless sub-path signal. A wireless sub-path signal corresponds to a scattering point of the sensing target. The scattering point is a location where the sensing target reflects and / or scatters the sensing signal.

[0052] In some embodiments, the wireless signal model is used to describe a sensing signal used to perform sensing measurements on a sensing target. In some embodiments, the wireless signal model can be used to describe the energy change between the transmitting end and the receiving end of the sensing signal used to perform sensing measurements on the sensing target.

[0053] In some embodiments, the first device may be a perception device, a perception management device, or a computer device unrelated to perception, and this application does not limit this.

[0054] In some embodiments, when the method is applied in an actual perception scenario, the first device may be a perception device or a perception management device. In some embodiments, the perception device is a device for sending and / or receiving perception signals. In some embodiments, the perception management device is configured to process data acquired based on the perception signals to obtain the desired perception data.

[0055] In some embodiments, this method is applied to actual sensing scenarios and can be used for clutter elimination. For example, in an environmental monitoring scenario, a sensing device is used to monitor the current room, which contains furniture and an occupant. If the occupant is resting in bed, and an intruder appears, the signal characteristics of the sensing signal reflected and / or scattered by the intruder will be different from those of the occupant. In this case, the sensing device can pre-record the signal characteristics of the sensing signal reflected and / or scattered by the occupant. When an intruder appears, the sensing device can exclude the sensing signal emitted and / or scattered by the occupant based on the pre-recorded signal characteristics of the sensing signal reflected and / or scattered by the occupant, thereby eliminating clutter and locating the intruder's location.

[0056] In some embodiments, the method is applied to a perception simulation scenario, and the first device may be a computer device used to simulate the perception scenario. For example, the first device may be a terminal device used to simulate the perception scenario, or a server providing services to the terminal device used to simulate the perception scenario.

[0057] In some embodiments, this method is applied to a perception simulation scenario and can be used to evaluate the performance of perception technologies. For example, software can be used to simulate the physical time of performance evaluation. After recording the transmitted signal, the software can simulate the output signal and perform perception technology processing based on the output signal, thereby enabling performance evaluation of the perception technology.

[0058] In some embodiments, a scattering point is a location where a sensing target reflects and / or scatters a sensing signal. After the sensing signal reaches the sensing target, it is reflected and / or scattered by the scattering point on the sensing target. Since the sensing target has multiple scattering points, the sensing signal is reflected and / or scattered in different directions by multiple scattering points, resulting in multiple wireless sub-path signals. Each wireless sub-path signal corresponds to a scattering point on the sensing target.

[0059] In some embodiments, because there are many locations on a sensing target that can reflect and / or scatter sensing signals, the sensing target can be abstracted and one or more scattering points can be selected to describe the sensing target, thereby simplifying the wireless signal model of the sensing target. For example, one scattering point can be selected to describe the sensing target. For example, five scattering points can be selected to describe the sensing target. Accordingly, the number of wireless subpath signals is the same as the number of scattering points.

[0060] In some implementations, the wireless signal model can be expressed using the following formula:

[0061] Among them, H tx,rx (t) represents the wireless signal model of the perceived target, G m (F m (t),t) represents the signal model of the wireless sub-path signal, F m (t) represents the impact model of the micro-motion of the perceived target on the perceived signal, m represents the mth wireless sub-path signal, and M represents the number of wireless sub-path signals.

[0062] In some embodiments, part or all of the at least one wireless sub-path signal respectively include a first parameter, where the first parameter is used to describe the effect of micro-motion of the perceived target on the perceived signal.

[0063] In some embodiments, the influence of the micro-motion of the perceived target on the perceived signal includes at least one of the following: the influence of the micro-motion of the perceived target on the energy of the perceived signal, the influence of the micro-motion of the perceived target on the phase of the perceived signal, and the influence of the micro-motion of the perceived target on the time delay of the perceived signal. The influence of the micro-motion of the perceived target on the energy of the perceived signal refers to the energy change, or the shift of the energy value, caused by the micro-motion of the perceived target after the perceived target is reflected and / or scattered by the scattering point. The influence of the micro-motion of the perceived target on the phase of the perceived signal refers to the phase change, or the phase shift, caused by the micro-motion of the perceived target after the perceived target is reflected and / or scattered by the scattering point. The influence of the micro-motion of the perceived target on the time delay of the perceived signal refers to the time delay caused by the micro-motion of the perceived target after the perceived target is reflected and / or scattered by the scattering point.

[0064] In some embodiments, all wireless sub-path signals in the at least one wireless sub-path signal respectively include the first parameter.

[0065] In some embodiments, some of the wireless sub-path signals in the at least one wireless sub-path signal respectively include a first parameter.

[0066] In some embodiments, some of the wireless sub-path signals in the at least one wireless sub-path signal may be one or multiple wireless sub-path signals.

[0067] In some embodiments, the wireless sub-path signal including the first parameter may be randomly determined or specially set.

[0068] For example, if the method is used in a primary assessment scenario of a sensing technology, such as a scenario where precise measurement of the sensing target is not required, the determination of which one or more of the at least one wireless subpath signals include the first parameter can be randomly determined. For example, the determination can be based on a random function.

[0069] For example, if this method is used for research with precise requirements, such as a scenario where refined measurement of a perception target is required, which one or several wireless sub-path signals in at least one wireless sub-path signal include the first parameter needs to be determined based on actual research needs.

[0070] In some embodiments, when the wireless signal model includes signal models of multiple wireless sub-path signals, the first parameters corresponding to the multiple wireless sub-path signals are the same.

[0071] In some embodiments, when the wireless signal model includes signal models of multiple wireless sub-path signals, at least two of the multiple wireless sub-path signals have different first parameters corresponding to them.

[0072] In some embodiments, when the wireless signal model includes signal models for multiple wireless sub-path signals, the first parameters corresponding to the multiple wireless sub-path signals are uniformly configured. In some embodiments, the first parameters corresponding to the multiple uniformly configured wireless sub-path signals are the same. For example, wireless sub-path signals 1 to 3 are uniformly configured, and the first parameters corresponding to wireless sub-path signals 1 to 3 are the same.

[0073] In some embodiments, when the wireless signal model includes signal models for multiple wireless sub-path signals, the first parameters corresponding to the multiple wireless sub-path signals are configured separately. In some embodiments, the first parameters corresponding to the multiple separately configured wireless sub-path signals may be the same or different. For example, wireless sub-path signals 1 to 3 are configured separately, wherein the first parameters corresponding to wireless sub-path signal 1 and wireless sub-path signal 2 are the same, and the first parameters corresponding to wireless sub-path signal 1 and wireless sub-path signal 3 are different.

[0074] In some embodiments, the signal model of the wireless sub-path signal is related to the moving speed of the sensing target.

[0075] In some embodiments, the signal model of the wireless sub-path signal can simulate the moving speed of the perception target, so that the wireless signal model of the perception target can take into account the moving speed of the perception target and achieve overall modeling of the perception target.

[0076] In some embodiments, the signal model of the wireless sub-path signal is also related to the following parameters: channel parameters from the transmitter of the perception signal to the perception target, channel parameters from the perception target to the receiver of the perception signal, the sending vector of the perception signal transmitter, the receiving vector of the perception target, the sending vector of the perception target, the receiving vector of the receiving end of the perception signal, the micro-motion model of the perception target, the distance from the transmitter of the perception signal to the perception target, the distance from the perception target to the receiver of the perception signal, the field strength diagram of the receiving antenna of the perception signal on the basic vectors of the ellipsoidal coordinates, the field strength diagram of the transmitting antenna of the perception signal on the basic vectors of the ellipsoidal coordinates, the horizontal angle of arrival of the perception signal, the vertical angle of arrival of the perception signal, the horizontal angle of departure of the perception signal, the vertical angle of departure of the perception target, the position of the receiving antenna of the perception signal, the position of the transmitting antenna of the perception signal, the cross-polarization power ratio, the wavelength of the perception signal, and the phase change of the perception signal.

[0077] In some embodiments, the wireless signal model of the sensing target is as follows:

[0078] It should be noted that and The two terms are in a multiplication relationship. Since the above formula is too long, in order to ensure its normal display in the document, a line break is added therein. For similar situations that occur in the embodiments of this application, the same understanding should be had as here, and this application will not go into details one by one.

[0079] Where u represents the receiving antenna of the sensing signal, s represents the transmitting antenna of the sensing signal, and M represents the number of wireless subpath signals. represents the channel between the transmitting antenna s of the sensing signal and the receiving antenna u of the sensing signal. The parameters of the channel from the transmitter of the sensing signal to the sensing target can be calculated by the position of the transmitter of the sensing signal and the sensing target. These are the channel parameters from the sensing target to the receiving end of the sensing signal. These parameters can be calculated through the position of the receiving end of the sensing signal and the sensing target. represents the sending vector of the transmitter of the perception signal, represents the receiving vector of the perceived target, represents the sending vector of the sensing target, represents the receiving vector of the receiving end of the sensing signal. m (t) represents the micro-motion model of the scattering point, d 3D F represents the sum of the distance from the transmitter of the perception signal to the perception target and the distance from the perception target to the receiver of the perception signal, and v represents the moving speed of the perception target. rx,u,θ and The receiving antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vectors θ and Field strength diagram on the tx,u,θ and The transmitting antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vector θ and Field strength diagram on . represents the horizontal arrival angle of the perceived signal, θ β,m,ZOA represents the vertical angle of arrival of the perceived signal, represents the horizontal departure angle of the perceived signal, θ α,m,ZOD Indicates the vertical departure angle of the perceived target, represents the location of the receiving antenna that senses the signal, represents the location of the transmitting antenna of the sensing signal, represents the cross-polarization power ratio, λ0 represents the wavelength of the perceived signal, Indicates the phase change of the perceived signal.

[0080] The technical solution provided by the embodiments of the present application constructs a wireless signal model of a perceived target using the signal model of at least one wireless subpath signal, where each wireless subpath signal corresponds to a scattering point. The signal model of the wireless subpath signal can simulate the micro-movements of the perceived target. Micro-movement modeling based on the wireless subpath signals better matches the actual local motion of the perceived target. By constructing a wireless signal model of the perceived target based on the signal model of at least one wireless subpath signal, the resulting wireless signal model is more compatible with the actual situation of the perceived target.

[0081] In some embodiments, the first parameter may be related to the phase, delay, RCS (Radar Cross Section) of the sensing signal, etc. In this regard, the embodiments of the present application provide the following exemplary methods.

[0082] Method 1: Phase correlation with the perceived signal

[0083] In some embodiments, the first parameter is related to a phase of the perception signal.

[0084] In some embodiments, the first parameter is determined based on the following parameters: the incident direction of the perception signal, the reflection direction of the perception signal, the micro-motion model of the scattering point, and the wavelength of the perception signal; wherein the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the perception node.

[0085] In some embodiments, a sensing node refers to a reference position of a scattering point during micromotion. For example, if the sensing target is chest movement, which rises and falls, then the sensing node can be a position during the chest's rise and fall. During chest movement, the relative displacement of the scattering point and this position can be considered a trigonometric function, so the micromotion model of the scattering point can be described using trigonometric functions.

[0086] In some embodiments, the first parameter is determined using the following formula:

[0087] Among them, F m (t) represents the first parameter, represents the incident direction of the sensing signal, Indicates the reflection direction of the sensing signal, f m (t) represents the micro-motion model of the scattering point, λ0 represents the wavelength of the perception signal, The micro-motion models representing the scattering points are mapped to the incident direction and the reflected direction of the perception signal respectively.

[0088] In some embodiments, the micro-motion of the perceived target may affect the phase of the perceived signal. Therefore, a phase change of the perceived signal may be provided as a first parameter to reflect the effect of the micro-motion of the perceived target on the perceived signal.

[0089] Method 2: Related to the delay of the perception signal

[0090] In some embodiments, the first parameter is related to a time delay of the perceived signal.

[0091] In some embodiments, the first parameter is determined based on at least one of the following parameters: a micro-motion model of the scattering point and a propagation speed of the sensing signal; wherein the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the sensing node.

[0092] In some embodiments, a sensing node refers to a reference position of a scattering point during micromotion. For example, if the sensing target is chest movement, which rises and falls, then the sensing node can be a position during the chest's rise and fall. During chest movement, the relative displacement of the scattering point and this position can be considered a trigonometric function, so the micromotion model of the scattering point can be described using trigonometric functions.

[0093] Exemplarily, the first parameter is determined using the following formula:

[0094] Among them, F m (t) represents the first parameter, f m (t) represents the micro-motion model of the scattering point, c represents the propagation speed of the perception signal, and δ represents the impulse function.

[0095] In some embodiments, when When F m (t)=1.

[0096] In some embodiments, the first parameter is determined based on the following parameters: a micro-motion model of the scattering point and a propagation speed of the sensing signal. For example, the first parameter is determined using the following formula:

[0097] Among them, F m (t) represents the first parameter, v represents the propagation speed of the perception signal, A b sin(2πf b t+φ b ) represents the micro-motion model of the scattering point, A b represents the motion amplitude of the scattering point, f b represents the movement frequency of the scattering point, φ b Represents the initial phase of the perception signal.

[0098] In some embodiments, the first parameter is determined according to the following parameters: a micro-motion model of the scattering points.

[0099] Exemplarily, the first parameter is determined using the following formula:

[0100] Among them, F m (t) represents the first parameter, A b sin(2πf b t+φ b ) represents the micro-motion model of the scattering point, A b represents the motion amplitude of the scattering point, f b represents the movement frequency of the scattering point, φ b Represents the initial phase of the perception signal.

[0101] In some embodiments, the time delay of the sensing signal can be determined based on the following parameters: the micro-motion model of the scattering point and the propagation speed of the sensing signal. For example, the time delay of the sensing signal is determined using the following formula: τ(t) = f m (t) / c

[0102] Among them, τ(t) represents the delay of the perception signal, f m (t) represents the micro-motion model of the scattering point, and c represents the propagation speed of the perception signal.

[0103] In some embodiments, the above-mentioned time delay of the sensed signal refers to the propagation delay of the sensed signal. In some embodiments, the time delay of the sensed signal will not be reflected in small scales.

[0104] Through the above method, the influence of the micro-motion of the scattering point on the perception signal can be reflected based on the delay change of the perception signal.

[0105] Method 3: Related to the RCS of the perceived signal

[0106] In some embodiments, the first parameter is related to the RCS of the perceived signal.

[0107] The radar cross section (RCS) is the equivalent area such that, when the radar energy intercepted by this area is isotropically scattered, the scattered power per unit solid angle is exactly equal to the power scattered per unit solid angle by the target toward the receiving antenna. Simply put, to compare the radar detectability of different objects, a benchmark is needed. Ideally, this benchmark should be independent of the frequency, polarization, or direction of incidence of the electromagnetic waves emitted by the radar, and ideally have a rigorous analytical solution. An ideal metal sphere meets this requirement. The RCS is expressed in units of cross-sectional area, so an ideal sphere with a cross-sectional area of ​​x has an RCS value of x. Similarly, if an object's RCS is y, it means that the object is as easily detected by radar as an ideal metal sphere with a cross-sectional area of ​​y.

[0108] In some embodiments, the first parameter is determined according to at least one of the following parameters: an energy change amount of the perception signal, and a phase change amount of the perception signal.

[0109] In some embodiments, the energy variation of the sensing signal refers to the energy variation of the sensing signal in two polarization directions caused by the micro-motion of the scattering point. The two polarization directions refer to the incident direction and the reflected direction of the sensing signal.

[0110] In some embodiments, the phase change of the sensing signal refers to the phase change of the sensing signal caused by the micro-motion of the scattering point after the sensing signal is reflected and / or scattered by the scattering point.

[0111] In some embodiments, the first parameter is determined using the following formula:

[0112] Among them, a m (t) and β m (t) represents the energy change of the perception signal caused by micro-motion, a m (t) and β m (t) are in two polarization directions, exp(jΦ m ) represents the phase change of the perception signal caused by micro-motion.

[0113] In some embodiments, the first parameter is determined according to a phase change of the sensed signal.

[0114] In some embodiments, the first parameter is determined according to an amount of energy variation of the sensed signal.

[0115] Through the above method, the influence of the micro-motion of the scattering point on the perception signal can be reflected based on the RCS of the perception signal.

[0116] For the micro-motion model of the scattering points mentioned in the above embodiments, this application also provides an exemplary embodiment.

[0117] In some embodiments, the micro-motion model of the scattering point includes at least one of the following parameters: the movement amplitude of the scattering point, the movement frequency of the scattering point, and the phase influence of the starting position of the scattering point on the perception signal.

[0118] In some embodiments, the phase influence of the starting position of the scattering point on the perception signal refers to the phase change of the perception signal caused by the reflection and / or scattering of the perception signal by the starting position of the scattering point.

[0119] Next, we will introduce the micro-motion model of scattering points with several specific examples.

[0120] 1. Breathing model

[0121] Assume that the amplitude of chest movement caused by human breathing is A b 5mm, frequency f b is 0.2Hz, and the chest movement caused by breathing conforms to a simple cosine relationship, so the breathing model can be modeled as: m (t) = A b sin(2πf b t+φ b )

[0122] Among them, A b =5mm, f b =0.2Hz,φ b = 0. φ b Represents the initial phase of the perception signal.

[0123] 2. Heartbeat Model

[0124] Assume that the amplitude of chest movement caused by human heartbeat is A h is 2mm, frequency f h is 1Hz, and the chest movement caused by the heartbeat conforms to a simple cosine relationship, so the heartbeat model can be modeled as: m (t) = A h sin(2πf h t+φ h )

[0125] Among them, A h =2mm,f h =1Hz,φ h = 0. φ h Represents the initial phase of the perception signal.

[0126] For the method provided in the embodiments of this application, this application also provides application examples in specific perception scenarios.

[0127] Example 1: Wireless signal model of a walking person

[0128] A first device determines a wireless signal model for a perceived target, where the wireless signal model is synthesized from multiple wireless sub-path signals. A first parameter is included for each of some or all of the wireless sub-path signals. The first parameter is used to describe the impact of micro-motions of the perceived target on the perceived signal.

[0129] Assume that the amplitude of chest movement caused by human breathing is A b 5mm, frequency f b The frequency is 0.2 Hz, and the chest movement caused by breathing conforms to a simple cosine relationship. For example, the wireless signal model is as follows:

[0130] Among them, A b =5mm, f b =0.2Hz,φ b = 0. φ b represents the initial phase of the sensing signal. m (t) The above indicates that the human body has multiple scattering points, one of which is used to simulate human breathing.

[0131] Where u represents the receiving antenna of the sensing signal, s represents the transmitting antenna of the sensing signal, and M represents the number of wireless subpath signals. represents the channel between the transmitting antenna s of the sensing signal and the receiving antenna u of the sensing signal. The parameters of the channel from the transmitter of the sensing signal to the sensing target can be calculated by the position of the transmitter of the sensing signal and the sensing target. These are the channel parameters from the sensing target to the receiving end of the sensing signal. These parameters can be calculated through the position of the receiving end of the sensing signal and the sensing target. represents the sending vector of the transmitter of the perception signal, represents the receiving vector of the perceived target, represents the sending vector of the sensing target, represents the receiving vector of the receiving end of the sensing signal. m (t) represents the micro-motion model of the scattering point, d 3D F represents the sum of the distance from the transmitter of the perception signal to the perception target and the distance from the perception target to the receiver of the perception signal, and v represents the moving speed of the perception target. rx,u,θ and The receiving antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vectors θ and Field strength diagram on the tx,u,θ and The transmitting antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vector θ and Field strength diagram on . represents the horizontal arrival angle of the perceived signal, θ β,m,ZOA represents the vertical angle of arrival of the perceived signal, represents the horizontal departure angle of the perceived signal, θ α,m,ZOD Indicates the vertical departure angle of the perceived target, represents the location of the receiving antenna that senses the signal, represents the location of the transmitting antenna of the sensing signal, represents the cross-polarization power ratio, λ0 represents the wavelength of the perceived signal, Indicates the phase change of the perceived signal.

[0132] Example 2: Wireless signal model of a walking person

[0133] A first device determines a wireless signal model for a perceived target, where the wireless signal model is synthesized from multiple wireless sub-path signals. A first parameter is included for each of some or all of the wireless sub-path signals. The first parameter is used to describe the impact of micro-motions of the perceived target on the perceived signal.

[0134] Assume that the amplitude of chest movement caused by human breathing is A b 5mm, frequency f b The frequency is 0.2 Hz, and the chest movement caused by breathing conforms to a simple cosine relationship. For example, the wireless signal model is as follows:

[0135] Among them, A b =5mm, f b =0.2Hz,φ b = 0. φ b represents the initial phase of the sensing signal. m (t) The above indicates that the human body has multiple scattering points, one of which is used to simulate human breathing.

[0136] Where u represents the receiving antenna of the sensing signal, s represents the transmitting antenna of the sensing signal, and M represents the number of wireless subpath signals. represents the channel between the transmitting antenna s of the sensing signal and the receiving antenna u of the sensing signal. The parameters of the channel from the transmitter of the sensing signal to the sensing target can be calculated by the position of the transmitter of the sensing signal and the sensing target. These are the channel parameters from the sensing target to the receiving end of the sensing signal. These parameters can be calculated through the position of the receiving end of the sensing signal and the sensing target. represents the sending vector of the transmitter of the perception signal, represents the receiving vector of the perceived target, represents the sending vector of the sensing target, represents the receiving vector of the receiving end of the sensing signal. m (t) represents the micro-motion model of the scattering point, d 3D F represents the sum of the distance from the transmitter of the perception signal to the perception target and the distance from the perception target to the receiver of the perception signal, and v represents the moving speed of the perception target. rx,u,θ and The receiving antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vectors θ and Field strength diagram on the tx,u,θ and The transmitting antenna of the sensing signal is located at the ellipsoidal coordinates of the basic vector θ and Field strength diagram on . represents the horizontal arrival angle of the perceived signal, θ β,m,ZOA represents the vertical angle of arrival of the perceived signal, represents the horizontal departure angle of the perceived signal, θ α,m,ZOD Indicates the vertical departure angle of the perceived target, represents the location of the receiving antenna that senses the signal, represents the location of the transmitting antenna of the sensing signal, represents the cross-polarization power ratio, λ0 represents the wavelength of the perceived signal, Indicates the phase change of the perceived signal.

[0137] It should be noted that, in Example 1, the first parameter is determined based on the micro-motion model of the scattering point; in Example 2, the first parameter is determined based on the micro-motion model of the scattering point and the propagation speed of the perception signal.

[0138] Example 3, sit-up model

[0139] Assume that the height h of an adult's upper body is 1m, and the height of the sensing node is As shown in Figure 3, point D is the sensing node, point O is the human hip, and point A is the head. The short arc AB represents the motion curve of the head during a sit-up. The length of DF is d = 5m or 25m. The wireless signal model for a sit-up is as follows:

[0140] in, T=3s,d f =10e 5 m. In addition, v can be calculated based on the movement frequency of the human body.

[0141] Wherein, Pathloss(t) (or PL) represents the energy change of the sensing signal, d0 represents the distance between the human body and the sensing node when the human body can reflect electromagnetic waves when it is lying down and standing up, d1 represents the distance between the human body and the sensing node when the human body can reflect electromagnetic waves when it is sitting up and lying down, and d f represents an infinite distance, which means that no electromagnetic wave echo can be generated or the echo is extremely weak and cannot be detected. T represents the time it takes to do a sit-up. d represents the distance from the sensing node to one end of the human head motion trajectory. h represents the height of the human upper body.

[0142] The first parameter in embodiment 3 is determined based on the energy variation of the perception signal.

[0143] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0144] Please refer to Figure 4, which shows a block diagram of a perceptual channel modeling apparatus provided by one embodiment of the present application. This apparatus has the functionality to implement the aforementioned perceptual channel modeling method example. This functionality can be implemented in hardware or by hardware executing corresponding software implementations. This apparatus can be the first device described above, or it can be provided within the first device. As shown in Figure 4, apparatus 400 may include a processing module 410.

[0145] Processing module 410 is used to determine a wireless signal model of a perception target, where the wireless signal model includes a signal model of at least one wireless subpath signal, where one wireless subpath signal corresponds to a scattering point of the perception target, and the scattering point is a location where the perception target reflects and / or scatters the perception signal.

[0146] In some embodiments, part or all of the at least one wireless sub-path signal respectively include a first parameter, where the first parameter is used to describe the impact of the micro-motion of the perceived target on the perceived signal.

[0147] In some embodiments, the first parameter is related to a phase of the perception signal.

[0148] In some embodiments, the first parameter is determined based on the following parameters: the incident direction of the perception signal, the reflection direction of the perception signal, the micro-motion model of the scattering point, and the wavelength of the perception signal; wherein the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the perception node.

[0149] In some embodiments, the first parameter is related to a delay of the perception signal.

[0150] In some embodiments, the first parameter is determined based on at least one of the following parameters: a micro-motion model of the scattering point and a propagation speed of the sensing signal; wherein the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the sensing node.

[0151] In some embodiments, the micro-motion model of the scattering point includes at least one of the following parameters: the movement amplitude of the scattering point, the movement frequency of the scattering point, and the phase influence of the starting position of the scattering point on the perception signal.

[0152] In some embodiments, the first parameter is related to an RCS of the perception signal.

[0153] In some embodiments, the first parameter is determined according to at least one of the following parameters: an energy change of the perception signal, and a phase change of the perception signal.

[0154] In some embodiments, when the wireless signal model includes signal models of multiple wireless sub-path signals, the first parameters corresponding to the multiple wireless sub-path signals are the same; or

[0155] Among the multiple wireless sub-path signals, at least two wireless sub-path signals respectively correspond to different first parameters.

[0156] In some embodiments, when the first parameter is a set value, the wireless sub-path signal corresponding to the first parameter is not affected by the micro-motion of the sensing target.

[0157] In some embodiments, the signal model of the wireless sub-path signal is related to the moving speed of the sensing target.

[0158] The technical solution provided by the embodiments of the present application constructs a wireless signal model of a perceived target using the signal model of at least one wireless subpath signal, where each wireless subpath signal corresponds to a scattering point. The signal model of the wireless subpath signal can simulate the micro-movements of the perceived target. Micro-movement modeling based on the wireless subpath signals better matches the actual local motion of the perceived target. By constructing a wireless signal model of the perceived target based on the signal model of at least one wireless subpath signal, the resulting wireless signal model is more compatible with the actual situation of the perceived target.

[0159] It should be noted that the device provided in the above embodiment only uses the division of the above-mentioned functional modules as an example to implement its functions. In actual applications, the above-mentioned functions can be assigned to different functional modules according to actual needs, that is, the content structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0160] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0161] Please refer to Figure 5, which shows a schematic diagram of the structure of a device provided by one embodiment of the present application. This device may be the first device described above. The device 500 may include a processor 501, a transceiver 502, and a memory 503. The transceiver 502 is configured to implement a transmission or reception function, and the processor 501 may be configured to implement other processing functions or control transmission and / or reception, such as implementing the functions of the processing module 410 described above.

[0162] The processor 501 includes one or more processing cores. The processor 501 executes various functional applications and information processing by running software programs and modules.

[0163] The transceiver 502 may include at least one of a receiver and a transmitter. For example, the receiver and the transmitter may be implemented as the same wireless communication component, which may include a wireless communication chip and a radio frequency antenna.

[0164] The memory 503 may be connected to the processor 501 and the transceiver 502 .

[0165] The memory 503 may be used to store a computer program executed by the processor, and the processor 501 is used to execute the computer program to implement each step in the above method embodiment.

[0166] In some embodiments, the processor 501 is used to determine a wireless signal model of a perception target, where the wireless signal model includes a signal model of at least one wireless sub-path signal, where a wireless sub-path signal corresponds to a scattering point of the perception target, and the scattering point is the location where the perception target reflects and / or scatters the perception signal.

[0167] For details not described in detail in this embodiment, please refer to the above embodiments and will not be described in detail here.

[0168] In addition, the memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, including but not limited to: magnetic or optical disks, electrically erasable programmable read-only memory, erasable programmable read-only memory, static access memory, read-only memory, magnetic memory, flash memory, and programmable read-only memory.

[0169] An embodiment of the present application also provides a computer-readable storage medium, in which a computer program is stored, and the computer program is used to be executed by a processor to implement the above-mentioned modeling method of the perception channel on the first device side. In some embodiments, the computer-readable storage medium may include: ROM (Read-Only Memory), RAM (Random-Access Memory), SSD (Solid State Drives) or optical disks, etc. Among them, random access memory may include ReRAM (Resistance Random Access Memory) and DRAM (Dynamic Random Access Memory).

[0170] An embodiment of the present application further provides a chip, which includes a programmable logic circuit and / or program instructions. When the chip is running, it is used to implement the above-mentioned modeling method of the perception channel on the first device side.

[0171] An embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. A processor reads and executes the computer program from the computer-readable storage medium to implement the above-mentioned modeling method of the perceptual channel on the first device side.

[0172] It should be understood that the "indication" mentioned in the embodiments of this application can be a direct indication, an indirect indication, or an indication of an association. For example, "A indicates B" can mean that A directly indicates B, for example, B can be obtained through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also mean that there is an association between A and B.

[0173] In the description of the embodiments of the present application, the term "corresponding" may indicate a direct or indirect correspondence between the two, or an association relationship between the two, or a relationship between indication and being indicated, configuration and being configured, etc.

[0174] In some embodiments of the present application, "predefined" may be implemented by pre-storing corresponding codes, tables, or other methods that can be used to indicate relevant information in a device (e.g., including the first device and the first core network element). The present application does not limit the specific implementation method. For example, predefined may refer to those defined in the protocol.

[0175] In some embodiments of the present application, the "protocol" may refer to a standard protocol in the field of communications, for example, it may include an LTE protocol, a NR protocol, and related protocols used in future communication systems, and this application does not limit this.

[0176] In this document, "plurality" refers to two or more. "And / or" describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. The character " / " generally indicates an "or" relationship between the associated objects.

[0177] The term “greater than or equal to” mentioned herein may mean greater than or equal to, or greater than, and the term “less than or equal to” may mean less than or equal to, or less than.

[0178] In addition, the step numbers described in this document only illustrate a possible execution order between the steps. In some other embodiments, the above steps may not be executed in the order of the numbers, such as two steps with different numbers are executed at the same time, or two steps with different numbers are executed in the opposite order of the diagram. The embodiments of the present application are not limited to this.

[0179] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0180] The above description is merely an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for modeling a sensing channel, characterized in that, The method is executed by a first device, and the method includes: Determine a wireless signal model of a sensing target, where the wireless signal model includes signal models of at least one wireless sub-path signal, and one wireless sub-path signal corresponds to a scattering point of the sensing target, and the scattering point is a position where the sensing target reflects and / or scatters a sensing signal.

2. The method according to claim 1, wherein Some or all of the at least one wireless sub-path signals respectively include a first parameter, and the first parameter is used to describe the influence of the micro-motion of the sensing target on the sensing signal.

3. The method according to claim 2, characterized in that, The first parameter is related to the phase of the sensing signal.

4. The method according to claim 3, characterized in that, The first parameter is determined according to the following parameters: the incident direction of the sensing signal, the reflection direction of the sensing signal, the micro-motion model of the scattering point, the wavelength of the sensing signal; where the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the sensing node.

5. The method according to claim 2, characterized in that The first parameter is related to the time delay of the sensing signal.

6. The method according to claim 5, characterized in that, The first parameter is determined according to at least one of the following parameters: the micro-motion model of the scattering point, the propagation speed of the sensing signal; where the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the sensing node.

7. The method according to claim 4 or 6, characterized in that The micro-motion model of the scattering point includes at least one of the following parameters: the motion amplitude of the scattering point, the motion frequency of the scattering point, the influence amount of the starting position of the scattering point on the phase of the sensing signal.

8. The method according to claim 2, wherein The first parameter is related to the radar cross section (RCS) parameter of the sensing signal.

9. The method according to claim 8, wherein The first parameter is determined according to at least one of the following parameters: the energy change amount of the sensing signal, the phase change amount of the sensing signal.

10. The method according to any one of claims 2 to 9, characterized in that In the case where the wireless signal model includes signal models of multiple wireless sub-path signals, The first parameters respectively corresponding to the multiple wireless sub-path signals are the same; or, There are at least two wireless sub-path signals among the multiple wireless sub-path signals whose respectively corresponding first parameters are different.

11. The method according to any one of claims 2 to 10, characterized in that, In the case where the first parameter is a set value, the wireless sub-path signal corresponding to the first parameter is not affected by the micro-motion of the sensing target.

12. The method according to any one of claims 1 to 11, characterized in that, The signal model of the wireless sub-path signal is related to the moving speed of the sensing target.

13. A modeling device for sensing a channel, characterized in that The device includes: A processing module, configured to determine a wireless signal model of a sensing target, where the wireless signal model includes signal models of at least one wireless sub-path signal, and one wireless sub-path signal corresponds to a scattering point of the sensing target, and the scattering point is a position where the sensing target reflects and / or scatters a sensing signal.

14. The device according to claim 13, characterized in that, Some or all of the at least one wireless sub-path signals respectively include a first parameter, and the first parameter is used to describe the influence of the micro-motion of the sensing target on the sensing signal.

15. The device according to claim 14, characterized in that, The first parameter is related to the phase of the sensing signal.

16. The device according to claim 15, characterized in that, The first parameter is determined according to the following parameters: the incident direction of the sensing signal, the reflection direction of the sensing signal, the micro-motion model of the scattering point, the wavelength of the sensing signal; where the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the sensing node.

17. The device according to claim 14, characterized in that, The first parameter is related to the time delay of the sensing signal.

18. The device according to claim 17, characterized in that, The first parameter is determined according to at least one of the following parameters: the micro-motion model of the scattering point, the propagation speed of the sensing signal; wherein, the micro-motion model of the scattering point is used to describe the relative motion between the scattering point and the sensing node.

19. The device according to claim 16 or 18, characterized in that, The micro-motion model of the scattering point includes at least one of the following parameters: the motion amplitude of the scattering point, the motion frequency of the scattering point, the phase influence amount of the starting position of the scattering point on the sensing signal.

20. The device according to claim 14, characterized in that The first parameter is related to the reflection cross-section parameter RCS of the sensing signal.

21. The device according to claim 20, characterized in that, The first parameter is determined according to at least one of the following parameters: the energy change amount of the sensing signal, the phase change amount of the sensing signal.

22. The device according to any one of claims 14 to 21, characterized in that, In the case where the wireless signal model includes the signal models of a plurality of the wireless sub-path signals, the first parameters respectively corresponding to the plurality of wireless sub-path signals are the same; or, there are at least two wireless sub-path signals among the plurality of wireless sub-path signals whose respectively corresponding first parameters are different.

23. The device according to any one of claims 14 to 22, characterized in that, When the first parameter is a set value, the wireless sub-path signal corresponding to the first parameter is not affected by the micro-motion of the sensing target.

24. The device according to any one of claims 13 to 23, characterized in that, The signal model of the wireless sub-path signal is related to the moving speed of the sensing target.

25. A device, characterized in that, The device includes a processor and a memory, and a computer program is stored in the memory, and the processor executes the computer program to implement the method according to any one of claims 1 to 12.

26. A computer-readable storage medium, characterized in that, A computer program is stored in the storage medium, and the computer program is used to be executed by a processor to implement the method according to any one of claims 1 to 12.

27. A chip, characterized in that, The chip includes a programmable logic circuit and / or program instructions, and is used to implement the method according to any one of claims 1 to 12 when the chip runs.

28. A computer program product, characterized in that, The computer program product includes computer instructions, the computer instructions are stored in a computer-readable storage medium, and the processor reads and executes the computer instructions from the computer-readable storage medium to implement the method according to any one of claims 1 to 12.

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