Clutter elimination method, device and equipment

Abstract

The invention provides a clutter elimination method, device and equipment, and the method comprises the steps: executing a 2D-FFT range and speed measurement algorithm for a normalized sensing signal matrix, and generating a first radar image; determining a distance estimation value and an echo signal attenuation factor estimation value of a clutter object through the first radar image; performing clutter elimination on the normalized sensing signal matrix according to the distance estimation value and the echo signal attenuation factor estimation value; according to the embodiment of the invention, a possible clutter object and a distance estimation value and an echo signal attenuation factor estimation value of the clutter object are identified according to a radar image generated by a 2D-FFT distance measurement and speed measurement algorithm; clutter elimination is carried out by using the distance estimation value and the echo signal attenuation factor estimation value, and a radar image without clutter echo influence is generated; therefore, echoes caused by clutter objects can be suppressed, interference of clutter echo sidelobes on the moving to-be-sensed target is avoided, and the probability of missed detection and the probability of false alarm are reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to a clutter elimination method, device and equipment. BACKGROUND

[0002] Integrated Sensing And Communication (ISAC) technology uses wireless communication electromagnetic waves to provide sensing services, which has been defined as one of the six application scenarios of 6G. Some ISAC applications only need to sense moving targets. For example, in the vehicle-to-everything (V2X) scenario, the moving vehicles are measured for distance and speed; in the unmanned aerial vehicle (UAV) scenario, the flying UAVs are measured for distance and speed; in the intrusion detection scenario, the moving targets trying to break into the specified area are sensed. For these applications, stationary objects are usually not the objects of interest of the ISAC system, and these stationary objects are called clutter objects.

[0003] For the ISAC system, the target to be detected is called a target to be sensed, and the target to be sensed is usually a moving target. For example, vehicles driving in the autonomous driving scenario, people walking in the indoor scenario, etc. However, there are many stationary objects around these targets to be sensed, such as the ground, the guardrails on both sides of the road, buildings and plants, walls and floors in the indoor scenario. The echoes caused by these stationary objects are called clutter, and these stationary objects are called clutter objects. Because the clutter objects usually have a large radar cross section, in the radar image generated by the ISAC system, the weak peak value caused by the target to be sensed may be covered by the strong peak value caused by the clutter object. This problem poses a serious challenge to moving target sensing, resulting in sensing deterioration problems such as "miss detection" and "false alarm". Miss detection refers to the echo of the target to be sensed being covered by the echo of the strong clutter object, resulting in the target to be sensed not being monitored. False alarm refers to the strong sidelobe of the clutter object echo being incorrectly identified as a target that does not actually exist, resulting in a false target sensing result.

[0004] The existing ISAC clutter processing method can only identify which are clutter objects and which are targets to be sensed, but cannot remove the miss detection and false alarm problems caused by the clutter object echo. SUMMARY

[0005] The embodiments of the present application aim to provide a clutter elimination method, device and equipment to solve the problem that the existing ISAC clutter processing method in the prior art cannot remove the miss detection and false alarm problems caused by the clutter object echo.

[0006] To solve the above problem, the embodiments of the present application provide a clutter elimination method, which comprises:

[0007] performing a 2D-FFT range-velocity algorithm on the normalized perception signal matrix to generate a first radar image;

[0008] determining, from the first radar image, a range estimate of the clutter object and an echo signal attenuation factor estimate of the clutter object;

[0009] performing clutter cancellation on the normalized perception signal matrix according to the range estimate and the echo signal attenuation factor estimate.

[0010] wherein the determining, from the first radar image, a range estimate of the clutter object and an echo signal attenuation factor estimate of the clutter object comprises:

[0011] determining the range estimate of the clutter object according to a horizontal axis coordinate of a peak value caused by the echo of the clutter object in the first radar image;

[0012] determining the echo signal attenuation factor estimate of the clutter object according to a vertical axis coordinate of the peak value caused by the echo of the clutter object in the first radar image.

[0013] wherein the performing clutter cancellation on the normalized perception signal matrix according to the range estimate and the echo signal attenuation factor estimate comprises:

[0014] constructing a clutter perception signal matrix of the clutter object according to the range estimate and the echo signal attenuation factor estimate;

[0015] obtaining a target perception signal matrix according to the normalized perception signal matrix and the clutter perception signal matrix;

[0016] performing a 2D-FFT range-velocity algorithm on the target perception signal matrix to obtain a radar image after clutter cancellation.

[0017] wherein the determining, from the first radar image, a range estimate of the clutter object and an echo signal attenuation factor estimate of the clutter object comprises:

[0018] determining a two-dimensional search space according to a peak value caused by the echo of the clutter object in the first radar image, wherein the two-dimensional search space is composed of a range search range of the clutter object and an echo signal attenuation factor search range of the clutter object;

[0019] determining a plurality of sets of range estimates and echo signal attenuation factor estimates contained in the two-dimensional search space according to a step size of the range search range and a step size of the echo signal attenuation factor search range.

[0020] wherein the performing clutter cancellation on the normalized perception signal matrix according to the range estimate and the echo signal attenuation factor estimate comprises:

[0021] In the two-dimensional search space, a plurality of clutter perception signal matrices are constructed according to a plurality of sets of distance estimation values and echo signal attenuation factor estimation values;

[0022] According to the normalized perception signal matrix and the plurality of clutter perception signal matrices, a plurality of target perception signal matrices are obtained;

[0023] A 2D-FFT ranging and velocity measurement algorithm is performed on the plurality of target perception signal matrices respectively, and a plurality of radar images are obtained;

[0024] According to the clutter elimination effect of the plurality of radar images, a radar image whose clutter elimination effect meets a preset condition is determined as a radar image after clutter elimination.

[0025] According to the normalized perception signal matrix and the clutter perception signal matrix, a target perception signal matrix is obtained, including:

[0026] The normalized perception signal matrix is subtracted from the clutter perception signal matrix to obtain the target perception signal matrix.

[0027] The method further includes:

[0028] Obtaining a transmitting end perception signal and a receiving end perception signal;

[0029] Dividing the receiving end perception signal by the corresponding transmitting end perception signal item by item to obtain the normalized perception signal matrix.

[0030] Embodiments of the present application also provide a clutter elimination device, the device comprising:

[0031] An image generation unit is configured to perform a two-dimensional fast Fourier transform (2D-FFT) ranging and velocity measurement algorithm on the normalized perception signal matrix to generate a first radar image;

[0032] A determination unit is configured to determine distance estimation values and echo signal attenuation factor estimation values of a clutter object through the first radar image;

[0033] A clutter elimination unit is configured to perform clutter elimination on the normalized perception signal matrix according to the distance estimation values and the echo signal attenuation factor estimation values.

[0034] Embodiments of the present application also provide a clutter elimination device, comprising a memory, a transceiver, and a processor:

[0035] The memory is configured to store a computer program; the transceiver is configured to transceive data under the control of the processor; and the processor is configured to read the computer program in the memory and perform the following operations:

[0036] perform a 2D-FFT ranging and velocity measurement algorithm on the normalized perception signal matrix to generate a first radar image;

[0037] determine, from the first radar image, a range estimate of the clutter object and an echo signal attenuation factor estimate of the clutter object;

[0038] perform clutter cancellation on the normalized perception signal matrix according to the range estimate and the echo signal attenuation factor estimate.

[0039] wherein the processor is further configured to read a computer program in the memory and perform the following operations:

[0040] determine, from a horizontal axis coordinate of a peak value caused by the echo of the clutter object in the first radar image, the range estimate of the clutter object;

[0041] determine, from a vertical axis coordinate of the peak value caused by the echo of the clutter object in the first radar image, the echo signal attenuation factor estimate of the clutter object.

[0042] wherein the processor is further configured to read a computer program in the memory and perform the following operations:

[0043] construct a clutter perception signal matrix of the clutter object according to the range estimate and the echo signal attenuation factor estimate;

[0044] obtain a target perception signal matrix according to the normalized perception signal matrix and the clutter perception signal matrix;

[0045] perform a 2D-FFT ranging and velocity measurement algorithm on the target perception signal matrix to obtain a radar image after clutter cancellation.

[0046] wherein the processor is further configured to read a computer program in the memory and perform the following operations:

[0047] determine a two-dimensional search space according to the peak value caused by the echo of the clutter object in the first radar image, wherein the two-dimensional search space is composed of a range search range of the clutter object and an echo signal attenuation factor search range of the clutter object;

[0048] determine a plurality of sets of range estimates and echo signal attenuation factor estimates contained in the two-dimensional search space according to a step size of the range search range and a step size of the echo signal attenuation factor search range.

[0049] wherein the processor is further configured to read a computer program in the memory and perform the following operations:

[0050] In the two-dimensional search space, a plurality of clutter perception signal matrices are constructed according to a plurality of sets of distance estimation values and echo signal attenuation factor estimation values;

[0051] According to the normalized perception signal matrix and the plurality of clutter perception signal matrices, a plurality of target perception signal matrices are obtained;

[0052] A 2D-FFT ranging and velocity measurement algorithm is performed on the plurality of target perception signal matrices respectively, and a plurality of radar images are obtained;

[0053] According to the clutter elimination effect of the plurality of radar images, a radar image whose clutter elimination effect meets a preset condition is determined as a radar image after clutter elimination.

[0054] The processor is further configured to read a computer program in the memory and perform the following operations:

[0055] The target perception signal matrix is obtained by subtracting the clutter perception signal matrix from the normalized perception signal matrix.

[0056] The processor is further configured to read a computer program in the memory and perform the following operations:

[0057] The transmitting-end perception signal and the receiving-end perception signal are obtained.

[0058] The receiving-end perception signal is divided by the corresponding transmitting-end perception signal item by item to obtain the normalized perception signal matrix.

[0059] The embodiments of the present application further provide a processor-readable storage medium, which stores a computer program, and the computer program is used to make the processor execute the method described above.

[0060] The embodiments of the present application further provide a computer program product, which comprises computer instructions, and the computer instructions are executed by the processor to realize the steps of the method described above.

[0061] The above technical solutions of the present application have at least the following beneficial effects:

[0062] In the clutter elimination method, device and equipment of the embodiments of the present application, the possible clutter objects and the distance estimation values and echo signal attenuation factor estimation values of the clutter objects are first identified according to the radar images generated by the 2D-FFT ranging and velocity measurement algorithm; the clutter elimination is performed by using the distance estimation values and the echo signal attenuation factor estimation values, and the radar images after eliminating the influence of the clutter echo are generated; thereby the echo caused by the clutter objects can be suppressed, the interference of the clutter echo sidelobe on the moving target to be perceived is avoided, and the miss detection probability and the false alarm probability are reduced. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 a block diagram representing a wireless communication system to which embodiments of the present application can be applied;

[0064] Figure 2 a flow chart representing steps of a clutter cancellation method provided by embodiments of the present application;

[0065] Figure 3 an example of a sensing signal distribution for a certain grid-shaped resource block in embodiments of the present application;

[0066] Figure 4 a schematic diagram representing a transmitter of a sensing and communication integrated transmitter end to transmit sensing and communication signals in the waveform shown in Figure 3

[0067] Figure 5 an example diagram representing a 2D-FFT ranging and velocity measurement algorithm;

[0068] Figure 6 a first radar image generated by performing a 2D-FFT ranging and velocity measurement algorithm on a normalized sensing signal matrix;

[0069] Figure 7 a radar image after a clutter cancellation method using a two-dimensional search space is applied; Figure 6 a clutter peak plot at a position of a velocity equal to 0;

[0070] Figure 8 one of radar images after a clutter cancellation method using a two-dimensional search space is applied;

[0071] Figure 9 the other of radar images after a clutter cancellation method using a two-dimensional search space is applied;

[0072] Figure 10 a structural schematic diagram of a clutter cancellation device provided by embodiments of the present application;

[0073] Figure 11 a structural schematic diagram of a clutter cancellation apparatus provided by embodiments of the present application. DETAILED DESCRIPTION

[0074] To make the technical problems solved by the present application, technical solutions and advantages clearer, specific embodiments will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0075] Figure 1 ​A block diagram of a wireless communication system to which embodiments of the present application can be applied is shown. The wireless communication system includes a terminal device 11 and a network side device 12. The terminal device 11 can also be referred to as a terminal or a user equipment (UE). It should be noted that the specific type of the terminal 11 is not limited in the embodiments of the present application. The network side device 12 can be a base station or a core network. It should be noted that the base station in the NR system is taken as an example in the embodiments of the present application, but the specific type of the base station is not limited.

[0076] The term “and / or” in the embodiments of the present application describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. The character “ / ” generally represents that the associated objects before and after it are in an “or” relationship.

[0077] The term “multiple” in the embodiments of the present application means two or more, and other quantifiers are similar.

[0078] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present application.

[0079] The technical solutions provided by the embodiments of the present application can be applied to various systems, especially 5G systems. For example, the applicable systems can be a global system of mobile communication (GSM) system, a code division multiple access (CDMA) system, a wideband code division multiple access (WCDMA) general packet radio service (GPRS) system, a long term evolution (LTE) system, an LTE frequency division duplex (FDD) system, an LTE time division duplex (TDD) system, a long term evolution advanced (LTE-A) system, a universal mobile system (UMTS), a worldwide interoperability for microwave access (WiMAX) system, a 5G new radio (NR) system, and the like. The various systems all include terminal devices and network devices. The system can also include a core network part, such as an evolved packet system (EPS), a 5G system (5GS), and the like.

[0080] The terminal device involved in the embodiments of the present application can refer to a device providing voice and / or data connectivity for a user, a handheld device with wireless connection function, or other processing devices connected to a wireless mediation device, etc. In different systems, the name of the terminal device can also be different. For example, in the 5G system, the terminal device can be called user equipment (UE). The wireless terminal device can communicate with one or more core networks (CN) through a radio access network (RAN). The wireless terminal device can be a mobile terminal device, such as a mobile phone (also known as a "cellular" phone) and a computer with a mobile terminal device, for example, it can be a portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile device that exchanges language and / or data with a radio access network. For example, personal communication service (PCS) phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), etc. The wireless terminal device can also be called a system, a subscriber unit, a subscriber station, a mobile station, a mobile, a remote station, an access point, a remote terminal, an access terminal, a user terminal, a user agent, a user device, which is not limited in the embodiments of the present application.

[0081] The network device related to the embodiments of the present application can be a base station, which can include multiple cells serving terminals. According to different application scenarios, the base station can also be referred to as an access point, or can be a device in an access network that communicates with wireless terminal devices through one or more sectors over an air interface, or other names. The network device can be used to exchange received air frames and Internet Protocol (IP) packets as a router between wireless terminal devices and the rest of the access network, which can include an Internet Protocol (IP) communication network. The network device can also coordinate the management of the properties of the air interface. For example, the network device related to the embodiments of the present application can be a network device (Base Transceiver Station, BTS) in the Global System for Mobile Communications (GSM) or Code Division Multiple Access (CDMA), or a network device (NodeB) in Wide-band Code Division Multiple Access (WCDMA), or an evolved network device (evolutional Node B, eNB or e-NodeB) in a long term evolution (LTE) system, or a 5G base station (gNB) in a next generation system, or a Home evolved Node B (HeNB), a relay node, a femto, a pico, etc., which are not limited in the embodiments of the present application. In some network structures, the network device can include a centralized unit (CU) node and a distributed unit (DU) node, and the centralized unit and the distributed unit can also be geographically separated.

[0082] The network device and the terminal device can each use one or more antennas for multi-input multi-output (MIMO) transmission, which can be single-user MIMO (SU-MIMO) or multiple-user MIMO (MU-MIMO). According to the shape and number of root antenna combinations, MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO, or massive-MIMO, or can be diversity transmission, precoding transmission, or beamforming transmission.

[0083] As shown in Figure 2 The method provided by the embodiment of the present application comprises:

[0084] Step 201: performing a two-dimensional fast Fourier transform (2D-FFT) ranging and velocity measurement algorithm on the normalized perception signal matrix to generate a first radar image;

[0085] Step 202: determining a distance estimation value and an echo signal attenuation factor estimation value of a clutter object through the first radar image;

[0086] Step 203: performing clutter elimination on the normalized perception signal matrix according to the distance estimation value and the echo signal attenuation factor estimation value.

[0087] The embodiment of the present application first identifies possible clutter objects and distance estimation values and echo signal attenuation factor estimation values of the clutter objects according to the first radar image generated by the 2D-FFT ranging and velocity measurement algorithm; performs clutter elimination using the distance estimation values and the echo signal attenuation factor estimation values to generate a radar image in which the influence of clutter echoes is eliminated; thereby the echoes caused by the clutter objects can be suppressed, so as to avoid the interference of clutter echo sidelobes on a moving target to be perceived, and reduce the probability of missed detection and the probability of false alarm. In addition, due to the non-mobility of fixed clutter objects, the processing of clutter suppression does not need to be real-time, and the process of clutter interference suppression does not need to be performed when a target to be perceived needs to be perceived, so that the time delay problem of perception will not be caused.

[0088] Optionally, the method further comprises:

[0089] acquiring a transmission-end perception signal and a reception-end perception signal;

[0090] dividing the reception-end perception signal by the corresponding transmission-end perception signal item by item to obtain the normalized perception signal matrix.

[0091] First, a brief description of the 2D-FFT ranging and velocity measurement algorithm is given:

[0092] OFDM(Orthogonal Frequency Division Multiplexing, Orthogonal Frequency Division Multiplexing) integrated sensing waveform In order to reduce the sensing signal overhead, the grid structure sensing signal distribution is adopted. Figure 3 The sensing signal distribution of a certain grid resource block is shown in the table 1. The red resource is used for sensing (i.e. the red resource is a sensing signal symbol, Sensing signal symbol), and the gray resource is used for communication (i.e. the gray resource is a communication symbol, communication symbol).

[0093] Table 1 Integrated sensing system parameters and parameter values

[0094] System parameters Symbols Parameter values Carrier frequency f c ]]> 28 GHz Bandwidth B 100 MHz Subcarrier spacing SCS (Af) 120 kHz Total number of subcarriers <![CDATA[N c ]]> 840 OFDM symbol duration [TECHNICAL FIELD] sym ]] 8.92 ps Sensing signal time duration [TECHNICAL FIELD] b ]] 7.5 ms T b the number of symbols within the inner <![CDATA[N sym ]]> 840 Number of sensing signals within bandwidth B <![CDATA[N f ]]> 120 T b interoceptive signal number <![CDATA[N t ]]> 120 Speed of light [cd] 3e8 m / s

[0095] As shown in Figure 4 The schematic diagram of the transmitter of the integrated sensing transmitting end transmitter sending the sensing and communication signals with the waveform shown in Figure 3

[0096] The transmitting end sensing signal d Tx (m,n) is transmitted by the transmitting antenna after IFFT(Inverse Fast Fourier Transform, Inverse Fast Fourier Transform), CP(Cyclic Prefix, Cyclic Prefix) insertion, digital-to-analog conversion. The sensing signal is reflected by the target to be sensed in space, and the echo is received by the receiving antenna, and after analog-to-digital conversion, CP removal, FFT(Fast Fourier Transform, Fast Fourier Transform), the receiving end sensing signal d Rx (m,n) is generated. Dividing d Rx (m,n) by d Tx (m,n) item by item can eliminate the data information carried by the sensing signal, and the normalized sensing signal matrix D can be obtained:

[0097]

[0098] Each column of the above matrix D represents the sensing signal on one OFDM symbol, and each row represents the sensing signal on one subcarrier. The column vector and the row vector respectively describe the phase shift caused by the distance and the Doppler frequency shift of the reflector in the matrix.

[0099] As shown in Figure 5 ​As shown, the 2D-FFT ranging and velocity measurement algorithm includes: first, performing IDFT (Inverse Discrete Fourier Transform) transformation on each column of data in the matrix D in formula (1), then performing DFT (Discrete Fourier Transform) transformation on each row of the column IDFT transformed result, and finally obtaining the matrix as the two-dimensional radar image in the distance and velocity domain.

[0100] For example, Figure 6 A first radar image generated by performing the 2D-FFT ranging and velocity measurement algorithm on the normalized sensing signal matrix is given. One of the static clutter objects has a distance of 25 meters and a speed of 0 m / s; and one of the to-be-sensed targets has a distance of 25 meters and a speed of 20 m / s. From the radar image Figure 5 It can be clearly seen from the radar image that the clutter interference affects the identification of the to-be-sensed target, and the to-be-sensed target is covered by the sidelobe of the clutter echo and is almost indistinguishable.

[0101] In order to suppress the clutter interference, the main idea of the present application is to eliminate the influence of the clutter object echo on the normalized sensing signal matrix, and then perform the conventional 2D-FFT ranging and velocity measurement algorithm. For example, Figure 6 As shown, only one clutter object and one moving to-be-sensed target scene is taken as an example, the element D m,n corresponding to the mth subcarrier and the nth sensing symbol on the normalized sensing signal matrix in formula (1) can be expressed as: m,n

[0102]

[0103] wherein A1 and R1 are the echo signal attenuation factor and distance of the clutter object respectively; A2, R2, and v2 are the echo signal attenuation factor, distance, and speed of the to-be-sensed target respectively. The echo signal attenuation factor A1 is determined by the radar cross section of the clutter object and the distance R1; since the clutter object is static, the echo signal part of the clutter object in formula (2) does not contain the power function component with speed (e 0 =1); z m,n is a Gaussian white noise; ω R , ω D are constants; Δf is the subcarrier spacing, c0 is the speed of light, T sym is the OFDM symbol length, and f c is the carrier frequency.

[0104] In at least one embodiment of the present application, step 202 includes:

[0105] ​The distance estimate of the clutter object is determined based on the horizontal axis coordinate of the peak value caused by the echo of the clutter object in the first radar image.

[0106] Based on the vertical axis coordinate of the peak value caused by the echo of the clutter object in the first radar image, the estimated value of the echo signal attenuation factor of the clutter object is determined.

[0107] Accordingly, step 203 includes:

[0108] Based on the distance estimate and the echo signal attenuation factor estimate, a clutter sensing signal matrix for the clutter object is constructed.

[0109] The target sensing signal matrix is ​​obtained based on the normalized sensing signal matrix and the clutter sensing signal matrix.

[0110] The target sensing signal matrix is ​​subjected to a 2D-FFT ranging and velocity measurement algorithm to obtain a radar image after clutter cancellation.

[0111] Optionally, the target sensing signal matrix is ​​obtained based on the normalized sensing signal matrix and the clutter sensing signal matrix, including:

[0112] The target sensing signal matrix is ​​obtained by subtracting the clutter sensing signal matrix from the normalized sensing signal matrix.

[0113] For example, the first radar image generated by the 2D-FFT ranging and velocity measurement algorithm first identifies potential clutter objects, along with estimated range and echo signal attenuation factors for these objects. Using these estimated range and echo signal attenuation factors, a clutter sensing signal matrix can be generated. Subtracting the clutter sensing signal matrix from the normalized sensing signal matrix, and then re-exercising the 2D-FFT algorithm on the resulting matrix (called the target sensing signal matrix), yields the radar image after clutter interference suppression, or the radar image after interference cancellation.

[0114] For example, an embodiment of this application provides a clutter cancellation method including:

[0115] Step S1: In the first radar image generated by the existing 2D-FFT ranging and velocity measurement algorithm, all L clutter objects are identified, with their indices l = 1, ..., L. Figure 6 Taking the scenario as an example, L=1. The distance estimate of the clutter object (l=1) is estimated using the first radar image. and estimated echo signal attenuation factor Distance estimate of clutter object l=1 From Figure 6 Obtain the horizontal axis coordinate of the peak value caused by the echo of the clutter object; estimate the attenuation factor of the echo signal from the clutter object at l=1. with Figure 6 The peak amplitude caused by the clutter object echo is proportional to the peak amplitude of the echo, which can be obtained by the peak amplitude estimation.

[0116] Step S2, subtracting the clutter perception signal matrix of the clutter object l=1 from the normalized perception signal matrix D in formula (1) and Constructing the clutter perception signal matrix of the clutter object l=1

[0117]

[0118] Step S3, subtracting the clutter perception signal matrix of formula (3) from the normalized perception signal matrix D in formula (1) The resulting matrix D2 is the perception signal matrix D2 corresponding to the target to be perceived l=2 (which can also be called the target perception signal matrix). If the distance estimation value of the clutter object l=1 and the echo signal attenuation factor estimation value are accurate enough, the influence of the clutter object l=1 in the normalized perception signal matrix D2 obtained from formula (4) can be basically ignored. At this time, in formula (4), only the target information to be perceived exists, and there is no information of the clutter object l=1.

[0119]

[0120] Step S4, performing a 2D-FFT algorithm on D2, so as to obtain the radar image after the clutter object l=1 interference suppression.

[0121] Step S5, if there are multiple clutter objects, repeating steps 1 to 4 for each clutter object until all clutter interferences are eliminated.

[0122] As can be seen from the steps of the above embodiment, the key to the clutter interference suppression effect of the clutter elimination method provided in the embodiment is the accurate estimation of the distance and echo signal attenuation factor of the clutter object. If the estimation accuracy of the distance and echo signal attenuation factor of the clutter object is poor, the final clutter suppression effect will be poor, and even greater interference will be caused. Therefore, the embodiment of the present application proposes a clutter elimination method based on a two-dimensional search space. Correspondingly, step 202 comprises:

[0123] According to the peak value caused by the clutter object echo in the first radar image, a two-dimensional search space is determined, wherein the two-dimensional search space is composed of a distance search range of the clutter object and an echo signal attenuation factor search range of the clutter object;

[0124] Based on the set step size of the distance search range and the step size of the echo signal attenuation factor search range, multiple sets of distance estimates and echo signal attenuation factor estimates contained in the two-dimensional search space are determined.

[0125] Step 203 includes:

[0126] In the two-dimensional search space, multiple clutter sensing signal matrices are constructed based on multiple sets of distance estimates and echo signal attenuation factor estimates.

[0127] Based on the normalized sensing signal matrix and multiple clutter sensing signal matrices, multiple target sensing signal matrices are obtained;

[0128] A 2D-FFT ranging and velocity measurement algorithm is executed on each of the target sensing signal matrices to obtain multiple radar images;

[0129] Based on the clutter cancellation effect of multiple radar images, the radar image whose clutter cancellation effect meets the preset conditions is determined as the radar image after clutter cancellation.

[0130] In the embodiments of this application, if only one estimation of the distance and echo signal attenuation factor is performed, it is difficult to obtain accurate distance estimates and echo signal attenuation factor estimates. For example, as Figure 7 As shown Figure 6 The clutter peak diagram at the location where the velocity equals 0 is shown, with the horizontal axis representing the distance sampling point and the vertical axis representing the echo signal intensity amplitude. Since the 2D-FFT ranging and velocimetry algorithm processes discrete signals, therefore... Figure 7 What can actually be obtained is the echo signal intensity amplitude at each FFT distance sampling point (bin index), i.e. Figure 7 The various black dots in the image. Although the embodiment of this application most desires to obtain the sampling point position and amplitude of the peak value of the black dashed line, the curve shown by the black dashed line cannot be obtained. Therefore, another clutter cancellation method provided by the embodiment of this application includes:

[0131] Step S6, by Figure 7 It can be seen that the peak value of the clutter echo occurs at sampling point 17, and the amplitude of the echo signal intensity at sampling point 16 is greater than that at sampling point 18. Therefore, it can be determined that the sampling point position representing the distance of the clutter object from the true peak value (i.e., the peak value of the black dashed line) is located between sampling points 16.5 and 17, corresponding to a distance of 24.55 meters to 25.3 meters. That is, the distance search range can be set to (24.55m, 25.3m).

[0132] Step S7, by Figure 7The echo signal strength amplitude of the clutter echo peak (sample point 17 position) is -20.5 dBm. The echo signal power at the peak position can be estimated, and a reasonable echo signal attenuation factor search range can be set, for example, (7.9 μW, 9.9 μW).

[0133] In step S8, according to the requirement of clutter interference elimination degree and the limitation of calculation complexity, a reasonable step length of the distance search range and a reasonable step length of the echo signal attenuation factor search range are selected. For example, the step length of the distance search range is set to 0.01 m, and 24.55 m, 24.56 m,..., 25.3 m need to be searched. A two-dimensional search space is formed by the distance search range and the echo signal attenuation factor search range.

[0134] In step S9, for each set of distance and echo signal attenuation factor in the two-dimensional search space, steps S2-S4 are repeatedly executed until a radar chart meeting the requirement of clutter interference elimination is searched.

[0135] For example, Figure 8 and Figure 9 respectively illustrate the clutter elimination method using the two-dimensional search space, and two sets of distance and echo signal attenuation factor combinations found in the two-dimensional search space. The first set of combinations can suppress the clutter echo by 10 dB, and the second set of combinations can suppress the clutter echo by 20 dB. Whether Figure 8 or Figure 9 , compared with the first radar chart obtained by the conventional 2D-FFT ranging and speed measurement algorithm (for example, Figure 6 ), because the clutter interference is suppressed, the peak of the target to be perceived at a distance of 25 m and a speed of 20 m / s is clearly visible, and the target to be perceived is more easily identified, and the occurrence of missed detection is avoided.

[0136] In summary, the embodiment of the present application first identifies the possible clutter object, the distance estimate value of the clutter object, and the echo signal attenuation factor estimate value according to the first radar chart generated by the 2D-FFT ranging and speed measurement algorithm; performs clutter elimination using the distance estimate value and the echo signal attenuation factor estimate value to generate a radar chart eliminating the influence of clutter echo; thereby the echo caused by the clutter object can be suppressed, the interference of the clutter echo sidelobe on the moving target to be perceived is avoided, and the missed detection probability and the false alarm probability are reduced. In addition, because the fixed clutter object is non-moving, the clutter suppression process does not need to be real-time, and the clutter interference suppression process does not need to be performed when the target to be perceived needs to be perceived, and therefore the time delay problem of perception is not caused.

[0137] As shown in Figure 10 , the embodiment of the present application further provides a clutter elimination device, which includes a memory 1020, a transceiver 1010, and a processor 1000:

[0138] a memory 1020 for storing a computer program; a transceiver 1010 for transceiving data under control of the processor 1000; and a processor 1000 for reading the computer program in the memory 1020 and performing the following operations:

[0139] performing a 2D-FFT ranging and velocity measurement algorithm on the normalized perception signal matrix to generate a first radar image;

[0140] determining, from the first radar image, a range estimate of the clutter object and an echo signal attenuation factor estimate of the clutter object;

[0141] performing clutter cancellation on the normalized perception signal matrix according to the range estimate and the echo signal attenuation factor estimate.

[0142] As an optional embodiment, the processor is further configured to read the computer program in the memory and perform the following operations:

[0143] determining, from a horizontal axis coordinate of a peak value caused by the echo of the clutter object in the first radar image, the range estimate of the clutter object;

[0144] determining, from a vertical axis coordinate of the peak value caused by the echo of the clutter object in the first radar image, the echo signal attenuation factor estimate of the clutter object.

[0145] As an optional embodiment, the processor is further configured to read the computer program in the memory and perform the following operations:

[0146] constructing a clutter perception signal matrix of the clutter object according to the range estimate and the echo signal attenuation factor estimate;

[0147] obtaining a target perception signal matrix according to the normalized perception signal matrix and the clutter perception signal matrix;

[0148] performing a 2D-FFT ranging and velocity measurement algorithm on the target perception signal matrix to obtain a radar image after clutter cancellation.

[0149] As an optional embodiment, the processor is further configured to read the computer program in the memory and perform the following operations:

[0150] determining a two-dimensional search space according to the peak value caused by the echo of the clutter object in the first radar image, wherein the two-dimensional search space is composed of a range search range of the clutter object and an echo signal attenuation factor search range of the clutter object;

[0151] According to the step length of the distance search range and the step length of the echo signal attenuation factor search range, a plurality of groups of distance estimation values and echo signal attenuation factor estimation values contained in the two-dimensional search space are determined.

[0152] As an optional embodiment, the processor is further configured to read the computer program in the memory and perform the following operations:

[0153] In the two-dimensional search space, a plurality of clutter perception signal matrices are constructed according to the plurality of groups of distance estimation values and echo signal attenuation factor estimation values.

[0154] According to the normalized perception signal matrix and the plurality of clutter perception signal matrices, a plurality of target perception signal matrices are obtained.

[0155] The 2D-FFT ranging and velocity measurement algorithm is performed on the plurality of target perception signal matrices respectively, and a plurality of radar images are obtained.

[0156] According to the clutter elimination effect of the plurality of radar images, the radar image whose clutter elimination effect meets the preset condition is determined as the radar image after clutter elimination.

[0157] As an optional embodiment, the processor is further configured to read the computer program in the memory and perform the following operations:

[0158] The target perception signal matrix is obtained by subtracting the clutter perception signal matrix from the normalized perception signal matrix.

[0159] As an optional embodiment, the processor is further configured to read the computer program in the memory and perform the following operations:

[0160] The transmit end perception signal and the receive end perception signal are obtained.

[0161] The receive end perception signal is divided by the corresponding transmit end perception signal item by item to obtain the normalized perception signal matrix.

[0162] Wherein, in Figure 10In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 1000) and memory (memory 1020). The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 1010 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. The processor 1000 is responsible for managing the bus architecture and general processing, and the memory 1020 can store data used by the processor 1000 during operation.

[0163] The processor 1000 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0164] This embodiment first identifies potential clutter objects and their estimated range and echo signal attenuation factor based on a first radar image generated by a 2D-FFT ranging and velocity measurement algorithm. Clutter cancellation is then performed using the estimated range and echo signal attenuation factor to generate a radar image free of clutter echoes. This suppresses echoes caused by clutter objects, preventing interference from clutter echo sidelobes to moving targets and reducing the probability of missed detections and false alarms. Furthermore, due to the immobility of stationary clutter objects, clutter suppression does not need to be performed in real-time; the clutter interference suppression process does not need to be executed when the target needs to be sensed, thus avoiding sensing delay issues.

[0165] It should be noted that the clutter cancellation device provided in this application embodiment is a device capable of performing the above-described clutter cancellation method. Therefore, all embodiments of the above-described clutter cancellation method are applicable to this device and can achieve the same or similar beneficial effects, which will not be repeated here.

[0166] like Figure 11 As shown in the figure, this application embodiment also provides a clutter cancellation device, the device comprising:

[0167] The image generation unit 1101 is configured to perform a 2D-FFT (2D-Fast Fourier Transform) range velocity algorithm on the normalized perception signal matrix to generate a first radar image.

[0168] The determination unit 1102 is configured to determine a distance estimation value and an echo signal attenuation factor estimation value of the clutter object based on the first radar image.

[0169] The clutter elimination unit 1103 is configured to eliminate the clutter based on the distance estimation value and the echo signal attenuation factor estimation value of the clutter object.

[0170] As an optional embodiment, the estimation unit comprises:

[0171] The first estimation sub-unit is configured to determine the distance estimation value of the clutter object based on the horizontal axis coordinate of the peak value caused by the echo of the clutter object in the first radar image.

[0172] The second estimation sub-unit is configured to determine the echo signal attenuation factor estimation value of the clutter object based on the vertical axis coordinate of the peak value caused by the echo of the clutter object in the first radar image.

[0173] As an optional embodiment, the clutter elimination unit comprises:

[0174] The first sub-unit is configured to construct a clutter perception signal matrix of the clutter object based on the distance estimation value and the echo signal attenuation factor estimation value.

[0175] The second sub-unit is configured to obtain a target perception signal matrix based on the normalized perception signal matrix and the clutter perception signal matrix.

[0176] The third sub-unit is configured to perform a 2D-FFT range velocity algorithm on the target perception signal matrix to obtain a radar image after clutter elimination.

[0177] As an optional embodiment, the estimation unit comprises:

[0178] The third estimation sub-unit is configured to determine a two-dimensional search space based on the peak value caused by the echo of the clutter object in the first radar image, wherein the two-dimensional search space is composed of a distance search range of the clutter object and an echo signal attenuation factor search range of the clutter object.

[0179] The fourth estimation sub-unit is configured to determine a plurality of sets of distance estimation values and echo signal attenuation factor estimation values contained in the two-dimensional search space based on a step length of the distance search range and a step length of the echo signal attenuation factor search range.

[0180] As an optional embodiment, the clutter elimination unit comprises:

[0181] a fourth sub-unit, configured to construct a plurality of clutter perception signal matrices according to a plurality of sets of distance estimation values and echo signal attenuation factor estimation values in the two-dimensional search space;

[0182] a fifth sub-unit, configured to obtain a plurality of target perception signal matrices according to the normalized perception signal matrix and the plurality of clutter perception signal matrices;

[0183] a sixth sub-unit, configured to perform a 2D-FFT ranging and velocity measurement algorithm on the plurality of target perception signal matrices respectively to obtain a plurality of radar images;

[0184] a seventh sub-unit, configured to determine, according to a clutter elimination effect of the plurality of radar images, a radar image with a clutter elimination effect satisfying a preset condition as a radar image after clutter elimination.

[0185] As an optional embodiment, the second sub-unit or the fifth sub-unit is further configured to:

[0186] subtract the clutter perception signal matrix from the normalized perception signal matrix to obtain the target perception signal matrix.

[0187] As an optional embodiment, the device further includes:

[0188] an acquisition unit, configured to acquire a transmitting-end perception signal and a receiving-end perception signal;

[0189] a calculation unit, configured to divide the receiving-end perception signal by the corresponding transmitting-end perception signal item by item to obtain the normalized perception signal matrix.

[0190] Embodiments of the present application first identify possible clutter objects and distance estimation values and echo signal attenuation factor estimation values of the clutter objects according to a first radar image generated by a 2D-FFT ranging and velocity measurement algorithm; perform clutter elimination by using the distance estimation values and the echo signal attenuation factor estimation values to generate a radar image after elimination of the influence of clutter echo; thereby the echo caused by the clutter objects can be suppressed, thereby avoiding the interference of clutter echo sidelobes on a moving target to be perceived, and reducing the probability of missed detection and the probability of false alarm. In addition, due to the non-mobility of fixed clutter objects, the processing of clutter suppression does not need to be real-time, and the process of clutter interference suppression does not need to be performed when a target to be perceived needs to be perceived, thus not causing the problem of time delay of perception.

[0191] It should be noted that the clutter elimination device provided by the embodiments of the present application is a device capable of performing the above-mentioned clutter elimination method, and all embodiments of the above-mentioned clutter elimination method are applicable to the device and can achieve the same or similar beneficial effects, which will not be repeated here.

[0192] It should be noted that the division of the unit in the embodiments of the present application is illustrative, and is only a logical function division. In actual implementation, another division manner can be used. In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0193] When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program code storage media.

[0194] The embodiments of the present application also provide a processor-readable storage medium, which stores a computer program. The computer program is used for causing the processor to execute each process in the method embodiments described above, and can achieve the same technical effects. To avoid repetition, details are not described herein. The processor-readable storage medium can be any available medium or data storage device accessible by the processor, including but not limited to a magnetic memory (such as a floppy disk, a hard disk, a magnetic tape, a magneto-optical disk (MO), etc.), an optical memory (such as a CD, a DVD, a BD, a HVD, etc.), and a semiconductor memory (such as a ROM, an EPROM, an EEPROM, a non-volatile memory (NAND FLASH), a solid state disk (SSD), etc.).

[0195] The embodiments of the present application also provide a computer program product, which includes computer instructions. When the computer instructions are executed by a processor, each process in the method embodiments described above is realized, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0196] Those skilled in the art will appreciate that embodiments of the present application can be readily used as software, hardware, or a combination of software and hardware. In one

[0197] The present application is described in reference to the flow diagrams and / or block diagrams of the methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flow diagrams and / or block diagrams, and combinations of blocks in the flow diagrams and / or block diagrams, can be implemented by computer executable instructions. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 an apparatus to perform the functions specified in the flow diagram and / or block diagram block or blocks.

[0198] These processor-executable instructions can also be loaded onto a computer or other programmable data processing devices, so that a series of operations are performed on the computer or other programmable data devices, to generate a computer-implemented process such that the instructions executed on the computer or other programmable devices provide steps for implementing the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 an apparatus to perform the functions specified in the flow diagram and / or block diagram block or blocks.

[0199] These processor-executable instructions can also be loaded onto a computer or other programmable data processing devices, so that a series of operations are performed on the computer or other programmable data devices, to generate a computer-implemented process such that the instructions executed on the computer or other programmable devices provide steps for implementing the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 an apparatus to perform the functions specified in the flow diagram and / or block diagram block or blocks.

[0200] Obviously, persons having ordinary skill in the art can make various modifications and variations without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims and their equivalents, it is intended that the present application encompass such modifications and variations.

Claims

1. A method of spurious signal elimination, characterized by, The method comprises: performing a two-dimensional fast Fourier transform (2D-FFT) ranging and velocity measurement algorithm on the normalized perception signal matrix to generate a first radar image; determining, from the first radar image, a distance estimate value and an echo signal attenuation factor estimate value of a clutter object; performing clutter cancellation on the normalized perception signal matrix according to the distance estimate value and the echo signal attenuation factor estimate value.

2. The method of claim 1, wherein, The determination of the distance estimate value and the echo signal attenuation factor estimate value of the clutter object from the first radar image comprises: determining the distance estimate value of the clutter object according to the horizontal axis coordinate of a peak value caused by the echo of the clutter object in the first radar image; determining the echo signal attenuation factor estimate value of the clutter object according to the vertical axis coordinate of the peak value caused by the echo of the clutter object in the first radar image.

3. The method of claim 2, wherein, The clutter cancellation on the normalized perception signal matrix according to the distance estimate value and the echo signal attenuation factor estimate value comprises: constructing a clutter perception signal matrix of the clutter object according to the distance estimate value and the echo signal attenuation factor estimate value; obtaining a target perception signal matrix from the normalized perception signal matrix and the clutter perception signal matrix; performing a 2D-FFT ranging and velocity measurement algorithm on the target perception signal matrix to obtain a radar image after clutter cancellation.

4. The method of claim 1, wherein, The determination of the distance estimate value and the echo signal attenuation factor estimate value of the clutter object from the first radar image comprises: determining a two-dimensional search space according to the peak value caused by the echo of the clutter object in the first radar image, wherein the two-dimensional search space is composed of a distance search range of the clutter object and an echo signal attenuation factor search range of the clutter object; determining a plurality of sets of distance estimate values and echo signal attenuation factor estimate values contained in the two-dimensional search space according to a step size of the distance search range and a step size of the echo signal attenuation factor search range.

5. The method of claim 4, wherein, The clutter cancellation on the normalized perception signal matrix according to the distance estimate value and the echo signal attenuation factor estimate value comprises: constructing a plurality of clutter perception signal matrices according to the plurality of sets of distance estimate values and echo signal attenuation factor estimate values in the two-dimensional search space; obtaining a plurality of target perception signal matrices from the normalized perception signal matrix and the plurality of clutter perception signal matrices; performing a 2D-FFT ranging and velocity measurement algorithm on each of the plurality of target perception signal matrices to obtain a plurality of radar images; determining, according to the clutter cancellation effects of the plurality of radar images, a radar image whose clutter cancellation effect meets a preset condition as a radar image after clutter cancellation.

6. The method according to claim 3 or 5, characterized in that, The obtaining of the target perception signal matrix from the normalized perception signal matrix and the clutter perception signal matrix comprises: subtracting the clutter perception signal matrix from the normalized perception signal matrix to obtain the target perception signal matrix.

7. The method of claim 1, wherein, The method further comprises: obtaining a transmitting-end perception signal and a receiving-end perception signal; dividing the receiving-end perception signal by the corresponding transmitting-end perception signal item by item to obtain the normalized perception signal matrix.

8. A spurious signal canceling device characterized by comprising: The device comprises: An image generation unit is configured to perform a 2D-FFT ranging and velocity measurement algorithm on the normalized perception signal matrix to generate a first radar image; A determination unit is configured to determine a distance estimation value and an echo signal attenuation factor estimation value of the clutter object based on the first radar image; A clutter elimination unit is configured to eliminate the clutter based on the distance estimation value and the echo signal attenuation factor estimation value.

9. A spurious signal canceling device characterized by comprising: The device comprises a memory, a transceiver and a processor: The memory is configured to store a computer program; the transceiver is configured to transceive data under the control of the processor; and the processor is configured to read the computer program in the memory and perform the following operations: perform a 2D-FFT ranging and velocity measurement algorithm on the normalized perception signal matrix to generate a first radar image; determine a distance estimation value and an echo signal attenuation factor estimation value of the clutter object based on the first radar image; eliminate the clutter based on the distance estimation value and the echo signal attenuation factor estimation value.

10. The spurious signal canceler of claim 9, wherein, The processor is further configured to read the computer program in the memory and perform the following operations: determine the distance estimation value of the clutter object based on the horizontal axis coordinate of the peak value caused by the echo of the clutter object in the first radar image; determine the echo signal attenuation factor estimation value of the clutter object based on the vertical axis coordinate of the peak value caused by the echo of the clutter object in the first radar image.

11. The spurious signal canceler of claim 10, wherein, The processor is further configured to read the computer program in the memory and perform the following operations: construct a clutter perception signal matrix of the clutter object based on the distance estimation value and the echo signal attenuation factor estimation value; obtain a target perception signal matrix based on the normalized perception signal matrix and the clutter perception signal matrix; perform a 2D-FFT ranging and velocity measurement algorithm on the target perception signal matrix to obtain a radar image after clutter elimination.

12. The spurious signal canceler of claim 9, wherein, The processor is further configured to read the computer program in the memory and perform the following operations: determine a two-dimensional search space based on the peak value caused by the echo of the clutter object in the first radar image, wherein the two-dimensional search space is composed of a distance search range of the clutter object and an echo signal attenuation factor search range of the clutter object; determine a plurality of sets of distance estimation values and echo signal attenuation factor estimation values contained in the two-dimensional search space based on a step size of the distance search range and a step size of the echo signal attenuation factor search range.

13. The spurious signal canceler of claim 12, wherein, The processor is further configured to read the computer program in the memory and perform the following operations: construct a plurality of clutter perception signal matrices based on the plurality of sets of distance estimation values and echo signal attenuation factor estimation values in the two-dimensional search space; obtain a plurality of target perception signal matrices based on the normalized perception signal matrix and the plurality of clutter perception signal matrices; perform a 2D-FFT ranging and velocity measurement algorithm on the plurality of target perception signal matrices respectively to obtain a plurality of radar images; determine a radar image whose clutter elimination effect meets a preset condition as the radar image after clutter elimination based on the clutter elimination effects of the plurality of radar images.

14. The spurious signal canceler of claim 11 or 13, wherein, The processor is further configured to read a computer program in the memory and perform the following operations: The processor is further configured to read a computer program in the memory and perform the following operations:

15. The spur cancellation device of claim 9, wherein, The processor is further configured to read a computer program in the memory and perform the following operations: Obtaining a transmitting end perception signal and a receiving end perception signal; Dividing the receiving end perception signal by the corresponding transmitting end perception signal to obtain the normalized perception signal matrix.

16. A processor-readable storage medium, characterized in that, The processor readable storage medium stores a computer program, and the computer program is configured to make the processor execute the method in any one of claims 1 to 7.

17. A computer program product, characterised in that, The computer program product comprises computer instructions, and the computer instructions are executed by the processor to implement the steps of the method in any one of claims 1 to 7.

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