Target Tracking Method, Device, Equipment and Storage Medium

Abstract

The present application provides a target tracking method, apparatus, device and storage medium. By determining the initial trajectory of the tracking target, then based on the differential velocity of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory, the initial trajectory is corrected to obtain the corrected trajectory of the initial trajectory. Finally, the tracking target is tracked according to the trajectory differential velocity of the corrected trajectory to determine the actual running trajectory of the tracking target. In this technical solution, the radar performs trajectory correction and target tracking based on the differential velocity of the trajectory, can obtain the accurate velocity and accurate azimuth information of the tracking target, improves the accuracy and reliability of target tracking, and reduces the probability of target misdetection.

Description

Technical Field

[0001] The present application relates to the technical field of signal processing, and particularly to a target tracking method, device, equipment and storage medium. Background Art

[0002] At present, time-division multiplexing multiple-in multiple-out (TDM-MIMO) radar can be used to detect targets. It mainly uses its multiple transmit antennas to alternately transmit signals to obtain high-resolution target angle measurement results in a working form. Since the TDM-MIMO radar reduces its sampling rate in slow time, the non-ambiguous velocity measurement range is significantly reduced, resulting in an easier occurrence of velocity ambiguity problems, which may lead to angle measurement deviations.

[0003] In the prior art, for the above-mentioned angle measurement deviation problem, the main solution is as follows: First, estimate the velocity-induced phase shift of the virtual array vector of the detection signal, use this velocity-induced phase shift to correct the phase of each element of the virtual array vector, and obtain the corrected virtual array vector. Secondly, perform the first Fourier transform on the corrected virtual array vector to generate the corrected virtual array spectrum, and based on the corrected virtual array spectrum, obtain the optimal compensation mode. Finally, use the optimal compensation mode to obtain the velocity and azimuth of the target, and then obtain the trajectory information of the target.

[0004] However, during the actual test process, due to the influence of various factors such as noise disturbance and hardware errors, the selected compensation mode may be incorrect, resulting in abnormal velocity and azimuth of the calculated target, and there is a problem of low target tracking accuracy in the existing target tracking method. Summary of the Invention

[0005] The present application provides a target tracking method, device, equipment and storage medium to overcome the problem of low target tracking accuracy in the existing target tracking method.

[0006] In a first aspect, an embodiment of the present application provides a target tracking method, including:

[0007] Determine the initial trajectory of the tracking target;

[0008] Based on the differential velocity of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory, correct the initial trajectory to obtain the corrected trajectory of the initial trajectory;

[0009] Track the tracking target according to the trajectory differential velocity of the corrected trajectory, and determine the actual running trajectory of the tracking target.

[0010] In a possible design of the first aspect, modifying the initial trajectory based on the differential velocity of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory to obtain the corrected trajectory of the initial trajectory includes:

[0011] Determine the differential velocity of the initial trajectory;

[0012] Determine the velocity error between the velocity corresponding to the candidate compensation mode of each trajectory point in the initial trajectory and the differential velocity of the initial trajectory;

[0013] Determine the candidate compensation mode corresponding to the velocity with the minimum velocity error as the optimal correction mode of the initial trajectory;

[0014] Use the velocity information and azimuth information corresponding to the optimal correction mode to correct the velocity information and azimuth information of each trajectory point in the initial trajectory to obtain the corrected trajectory of the initial trajectory.

[0015] Optionally, tracking the tracking target according to the trajectory differential velocity of the corrected trajectory to determine the actual running trajectory of the tracking target includes:

[0016] Determine the optimal tracking compensation mode of the tracking target at the next moment according to the trajectory differential velocity of the corrected trajectory;

[0017] Based on the velocity information and azimuth information corresponding to the optimal tracking compensation mode, determine the target trajectory point of the tracking target at the next moment;

[0018] Use the velocity information and azimuth information corresponding to the optimal tracking compensation mode to correct the velocity information and azimuth information of the target trajectory point;

[0019] Use the velocity information and azimuth information of the corrected target trajectory point to update the trajectory of the tracking target to obtain the actual running trajectory of the tracking target.

[0020] In another possible design of the first aspect, determining the initial trajectory of the tracking target includes:

[0021] Determine the trajectory starting point of the tracking target;

[0022] Determine the target points of the same target at different times that match the trajectory starting point as trajectory points;

[0023] Generate the initial trajectory of the tracking target according to the trajectory starting point and the determined preset number of trajectory points. The number of trajectory points on the initial trajectory meets the quantity requirement, and the initial trajectory meets the preset smoothing condition.

[0024] Optionally, determining target points at different times of the same target that match the trajectory starting point as trajectory points includes:

[0025] Performing neighborhood point association based on the speed information, azimuth information corresponding to the optimal compensation mode determined for the trajectory starting point, and the frame interval information of the tracking target, and sequentially determining a second trajectory point that matches the trajectory starting point and a third trajectory point that matches the second trajectory point until a preset number of trajectory points are determined.

[0026] In another possible design of the first aspect, before determining the initial trajectory of the tracking target, the method further includes:

[0027] Clustering the target point cloud of the tracking target at the same time according to the determined candidate compensation modes respectively, to obtain a target clustering result corresponding to each candidate compensation mode, where the target clustering result includes speed information and azimuth information corresponding to the candidate compensation mode.

[0028] Optionally, before clustering the target point cloud of the tracking target at the same time according to the determined candidate compensation modes respectively to obtain a target clustering result corresponding to each candidate compensation mode, the method further includes:

[0029] Obtaining multiple frames of radar signals of the tracking target, and respectively determining the power diagrams of each frame of radar signals;

[0030] According to the power diagrams of each frame of radar signals, determining the target points of the tracking target at different times;

[0031] Performing trajectory association on the target points of the tracking target at different times according to the time sequence of each frame of radar signals, and determining the estimated motion speed and estimated motion direction of the tracking target;

[0032] Filtering out candidate compensation modes from a preset plurality of compensation modes according to the estimated motion speed and estimated motion direction of the tracking target;

[0033] Determining an optimal compensation mode according to the virtual array spectra under each compensation mode in the candidate compensation modes.

[0034] In a second aspect, an embodiment of the present application provides a target tracking device, including:

[0035] A determination module, configured to determine an initial trajectory of a tracking target;

[0036] A processing module, configured to correct the initial trajectory based on the differential speed of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory, to obtain a corrected trajectory of the initial trajectory;

[0037] A tracking module, configured to track the tracking target according to the trajectory differential velocity of the corrected trajectory, and determine the actual running trajectory of the tracking target.

[0038] In a possible design of the second aspect, the processing module is specifically configured to:

[0039] Determine the differential velocity of the initial trajectory;

[0040] Determine the velocity error between the velocity corresponding to the candidate compensation mode of each trajectory point in the initial trajectory and the differential velocity of the initial trajectory;

[0041] Determine the candidate compensation mode corresponding to the velocity with the minimum velocity error as the optimal correction mode of the initial trajectory;

[0042] Use the velocity information and azimuth information corresponding to the optimal correction mode to correct the velocity information and azimuth information of each trajectory point in the initial trajectory, and obtain the corrected trajectory of the initial trajectory.

[0043] Optionally, the tracking module is specifically configured to:

[0044] Determine the optimal tracking compensation mode of the tracking target at the next moment according to the trajectory differential velocity of the corrected trajectory;

[0045] Based on the velocity information and azimuth information corresponding to the optimal tracking compensation mode, determine the target trajectory point of the tracking target at the next moment;

[0046] Use the velocity information and azimuth information corresponding to the optimal tracking compensation mode to correct the velocity information and azimuth information of the target trajectory connection point;

[0047] Use the velocity information and azimuth information of the corrected target trajectory point to update the trajectory of the tracking target, and obtain the actual running trajectory of the tracking target.

[0048] In another possible design of the second aspect, the determining module is specifically configured to:

[0049] Determine the trajectory starting point of the tracking target;

[0050] Determine the target points of the same target at different times that match the trajectory starting point as trajectory points;

[0051] Generate the initial trajectory of the tracking target according to the trajectory starting point and the determined preset number of trajectory points, the number of trajectory points on the initial trajectory meets the quantity requirement, and the initial trajectory meets the preset smooth condition.

[0052] Optionally, the determining module is configured to determine target points of the same target at different times that match the trajectory starting point as trajectory points. Specifically:

[0053] The determining module is specifically configured to perform neighborhood point association based on the speed information, azimuth information corresponding to the optimal compensation mode determined for the trajectory starting point, and the frame interval information of the tracking target, and sequentially determine a second trajectory point that matches the trajectory starting point and a third trajectory point that matches the second trajectory point until a preset number of trajectory points are determined.

[0054] In another possible design of the second aspect, the processing module is further configured to, before the determining module determines the initial trajectory of the tracking target, cluster the target point clouds of the tracking target at the same time according to the determined candidate compensation modes, and obtain a target clustering result corresponding to each candidate compensation mode. The target clustering result includes the speed information and azimuth information corresponding to the candidate compensation mode.

[0055] Optionally, the processing module is further configured to perform the following steps before clustering the target point clouds of the tracking target at the same time according to the determined candidate compensation modes to obtain a target clustering result corresponding to each candidate compensation mode:

[0056] Obtain multiple frames of radar signals of the tracking target, and respectively determine the power diagrams of each frame of radar signals;

[0057] According to the power diagrams of each frame of radar signals, determine the target points of the tracking target at different times;

[0058] According to the time sequence of each frame of radar signals, perform trajectory association on the target points of the tracking target at different times, and determine the estimated motion speed and estimated motion direction of the tracking target;

[0059] According to the estimated motion speed and estimated motion direction of the tracking target, screen out candidate compensation modes from a preset plurality of compensation modes;

[0060] According to the virtual array spectra under each compensation mode in the candidate compensation modes, determine the optimal compensation mode.

[0061] In a third aspect, an embodiment of the present application provides a detection device, including: a processor, a memory, a transceiver, and computer program instructions stored on the memory and executable on the processor. When the processor executes the computer program instructions, the methods described in the first aspect and all possible designs above are implemented.

[0062] Fourthly, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method as described in the first aspect and all possible designs above.

[0063] Fifthly, an embodiment of the present application provides a computer program product, including: a computer program. When the computer program is executed by a processor, it is used to implement the method as described in any one of the first aspect and all possible designs above.

[0064] Sixthly, an embodiment of the present application provides a program. When the program is executed by a processor, it is used to execute the method as described in the first aspect.

[0065] Seventhly, an embodiment of the present application provides a chip, including: a processing module and a communication interface. The processing module can execute the method as described in the first aspect.

[0066] Further, the chip further includes a storage module (such as, a memory). The storage module is used to store instructions, and the processing module is used to execute the instructions stored in the storage module. And the execution of the instructions stored in the storage module enables the processing module to execute the method as described in the first aspect.

[0067] The target tracking method, device, equipment and storage medium provided by the embodiments of the present application determine the initial trajectory of the tracking target, and then correct the initial trajectory based on the differential speed of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory to obtain the corrected trajectory of the initial trajectory. Finally, the tracking target is tracked according to the trajectory differential speed of the corrected trajectory to determine the actual running trajectory of the tracking target. In this technical solution, the radar performs trajectory correction and target tracking based on the differential speed of the trajectory, can obtain accurate speed and accurate azimuth information of the tracking target, improves the accuracy and reliability of target tracking, and reduces the probability of target misdetection. Description of the Drawings

[0068] Figure 1 It is a schematic diagram of the antenna arrangement of an FMCW radar;

[0069] Figure 2 is Figure 1 a schematic diagram of the signal timing diagram of the transmitted signal of the transmitting antenna of the FMCW radar shown;

[0070] Figure 3 It is a schematic flowchart of the first embodiment of the target tracking method provided by the embodiment of the present application;

[0071] Figure 4 is the information of a single target point of the tracking target;

[0072] Figure 5Schematic flowchart of the second embodiment of the target tracking method provided by the embodiments of the present application;

[0073] Figure 6 Schematic flowchart of the third embodiment of the target tracking method provided by the embodiments of the present application;

[0074] Figure 7 Schematic flowchart of the fourth embodiment of the target tracking method provided by the embodiments of the present application;

[0075] Figure 8 Schematic diagram of the association of the trajectory starting point;

[0076] Figure 9 Schematic diagram of generating an initial trajectory based on the optimal compensation mode of the trajectory starting point;

[0077] Figure 10 Schematic flowchart of the fifth embodiment of the target tracking method provided by the embodiments of the present application;

[0078] Figure 11 Schematic structural diagram of the target tracking device embodiment provided by the embodiments of the present application;

[0079] Figure 12 Schematic structural diagram of the detection device provided by the embodiments of the present application. Detailed implementation manners

[0080] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are some but not all of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the scope of protection of the present application.

[0081] Before introducing the application background and technical solutions of the present application, the terms involved in the embodiments of the present application will be explained first:

[0082] Radar: Radar is an electronic device that uses electromagnetic waves to detect targets. By emitting electromagnetic waves to irradiate the targets and receiving their echoes, information such as the distance from the target to the electromagnetic wave emission point, the rate of change of distance (radial velocity), azimuth, altitude, etc. can be obtained, and thus the tracking of the targets can be achieved.

[0083] MIMO radar: Multiple-input multiple-output radar, also known as multiple-transmit multiple-receive radar, is a type of radar that improves the angle estimation ability of the radar. Currently, MIMO radar mainly adopts several specific forms such as frequency division multiplexing (FDM), code division multiplexing (CDM), and time division multiplexing (TDM) to achieve multiple transmit and multiple receive.

[0084] In practical applications, considering the cost limitations and implementation complexity of semiconductor devices, TDM-MIMO technology is currently basically adopted for millimeter-wave radars. It can be understood that in the embodiments of this application, unless otherwise specified, the MIMO radar mentioned refers to the TDM-MIMO radar.

[0085] Velocity ambiguity: The phenomenon of confusion in the measured target velocity caused by spectrum overlap, making it difficult to distinguish the true velocity of the target. Especially for TDM-MIMO radars, due to the reduction of the sampling rate in slow time, the non-ambiguous velocity measurement range is significantly reduced, resulting in a more likely occurrence of velocity ambiguity problems.

[0086] Slow time and fast time

[0087] In practical applications, when the radar operates, it periodically transmits pulse signals and samples the echo signals during the pulse interval. Although the echo sampling interval and the pulse repetition interval (pulse period) are on the same time axis, there is a very large difference in magnitude. The echo sampling interval is approximately on the order of 10 -8 order of magnitude, while the pulse repetition period is approximately on the order of 10 -3 order of magnitude. Therefore, it may be inconvenient to process. So the echo sampling interval and the pulse repetition period are divided into two dimensions, which are respectively called fast time and slow time. The echo within each pulse interval is segmented as a row, and the sampled echo signals are stored in the form of a two-dimensional array, with the horizontal and vertical axes being fast time and slow time respectively. Generally speaking, fast time is the time of a single pulse, and slow time is the time of a pulse train.

[0088] Point cloud data: It is a collection of a large number of point clouds on the surface characteristics of the target. In the prior art, laser scanning is mostly used to obtain the point cloud data of the environment; when a laser beam irradiates the target surface, the reflected laser will carry information such as azimuth and distance. If the laser beam is scanned along a certain trajectory, the information of the reflected laser points will be recorded while scanning. Since the scanning is extremely fine, a large number of laser points can be obtained, and thus the laser point cloud data of the target can be formed.

[0089] At the current stage, the antennas of current millimeter-wave radars generally adopt the multiple transmit and multiple receive (MIMO) form. By means of virtual array elements, the actual size of the antenna is effectively reduced, and then high-resolution target angle measurement results similar to those of large-sized antennas can be obtained. Exemplarily, assume that the MIMO radar includes M transmit antennas and N receive antennas, where M and N are integers greater than or equal to 1. By reasonably designing the spacing between the transmit antennas and the spacing between the receive antennas, the effect of 1 transmit and M*N receive can be achieved.

[0090] Assume that the spacing between adjacent transmitting antennas is D, and the spacing between adjacent receiving antennas is d. To ensure no antenna grating lobes, it is generally required that d ≤ 0.5λ, where λ is the wavelength of the radar. To maximize the utilization of the antenna aperture, during design, the spacing between transmitting antennas and the spacing between receiving antennas generally need to satisfy D = Nd.

[0091] Exemplarily, the following takes the target detection of a frequency modulated continuous wave (FMCW) radar as an example for explanation. The basic transmitted signal of an FMCW radar is a frequency ramp (usually also called a chirp, which is a signal whose frequency changes linearly with time). Exemplarily, Figure 1 It is a schematic diagram of the antenna arrangement of an FMCW radar. Figure 2 For Figure 1 It is a schematic diagram of the signal timing of the transmitted signal of the shown FMCW radar. As Figure 1 shown, this FMCW radar is explained with an antenna array of 2 transmitters and 4 receivers. That is, the antenna array of this FMCW radar includes 2 transmitting antennas and 4 receiving antennas. The spacing between the 2 transmitting antennas is D, and the spacing between two adjacent receiving antennas is d. Correspondingly, according to D = Nd satisfied by the spacing D between transmitting antennas and the spacing d between receiving antennas, this antenna array can form an equivalent receiving array.

[0092] Optionally, as Figure 2 shown, based on Figure 1 the shown equivalent receiving array, the signal transmitted by the transmitting antenna of the FMCW radar is a frequency ramp signal whose frequency changes linearly with time.

[0093] As known from the above Figure 2 it can be seen that multiple transmitting antennas of the antenna array of a MIMO radar can adopt an operating form of alternately transmitting signals. However, when there is relative motion between the radar and the detected target, the phase of the continuous echo will change with the samples continuously, that is, the signal in the slow time dimension will have a non-zero Doppler bandwidth. At this time, the phase change amount brought by the Doppler frequency of the moving target within the switching time of different transmitting antennas will be coupled to each receiving antenna, affecting the correct synthesis of the receiving antenna aperture. In addition, due to the TDM characteristic of the MIMO radar reducing the sampling rate in the slow time, the unambiguous velocity measurement range is significantly reduced, and once velocity ambiguity occurs, it will further cause deviation in angle measurement.

[0094] To address the above technical problems, the prior art has proposed a velocity deblurring algorithm. Optionally, the signal received by the equivalent receiving array of the radar can be represented in the form of a virtual array element vector. Therefore, the implementation principle of the existing velocity deblurring algorithm is as follows:

[0095] Step 1: Estimate the velocity-induced phase shift of the virtual array element vector S of the received signal

[0096] where is the phase difference of the continuous chirp (frame) emitted from adjacent transmit antennas and at the receiver. This velocity-induced phase shift is related to the true velocity v of the target true . Since the estimated velocity v of the target obtained based on the power diagram of the received signal est may have velocity ambiguity, therefore, the value of the true velocity v of the target true is unknown. However, according to the properties of the power diagram and the estimated velocity, the possible value set of the true velocity v of the target true is v true ∈{v est , v est +2v max , v est -2v max}, where v max is the maximum moving velocity of the target. Thus, the relationship between the true velocity of the target and the estimated velocity of the target can be expressed by the following formula: v true =v est +2xv max , x∈R. However, in actual application scenarios, the value of x being {0, -1, 1} can meet the requirements. In addition, the value of x in the MIMO algorithm is also restricted by the transmit antennas.

[0097] In this embodiment, according to different values of the true velocity of the target, different velocity-induced phase shifts can be obtained. For example, when v true =v est , the obtained velocity-induced phase shift is This corresponding transmit antenna compensation mode is called compensation mode 0; when v true =v est +2v max , the obtained velocity-induced phase shift is This corresponding transmit antenna compensation mode is called compensation mode 1; when v true =v est -2v max , the obtained velocity-induced phase shift is This corresponding transmit antenna compensation mode is called compensation mode 2.

[0098] It can be understood that in step 1, the velocity-induced phase shift can be obtained by the formula , and the maximum moving velocity v of the target maxIt can be determined by the following formula: where λ is the wavelength of the radar, and T c is a chirp period. In Figure 2 when the radar has 2 transmitting antennas, T c = 2T.

[0099] Step 2: Use to correct the phase of each element in the virtual array vector S, and obtain the corrected virtual array vector S c .

[0100] In this step, based on different compensation modes, the corrected virtual array vector S under different compensation modes can be obtained c . For example, compensation mode 0 corresponds to the corrected virtual array vector S c0 , compensation mode 1 corresponds to the corrected virtual array vector S c1 , and compensation mode 2 corresponds to the corrected virtual array vector S c2 .

[0101] Optionally, for a MIMO radar with M transmitting antennas and N receiving antennas, the phase of the virtual array vector S can be expressed by the following formula:

[0102]

[0103] where is the phase caused by the path difference between adjacent receiving antennas, θ is the azimuth angle of the target, is the phase change amount brought by the Doppler frequency of the target during the switching time between adjacent transmitting antennas.

[0104] After the corrected virtual array vector S c can be expressed by the following formula:

[0105]

[0106] In practical applications, if the virtual array vector can be corrected correctly, that is, the phase introduced by the Doppler effect between the transmitting antennas can be eliminated, then at this time, the corrected virtual array vector S c can be expressed by the following formula:

[0107]

[0108] Step 3: Perform the first Fourier transform on the corrected virtual array vector S c to generate the corrected virtual array spectrum P c .

[0109] Optionally, different compensation modes correspond to different virtual array spectra. For example, compensation mode 0 corresponds to virtual array spectrum P c0 , compensation mode 1 corresponds to virtual array spectrum P c1 , compensation mode 2 corresponds to virtual array spectrum P c2 .

[0110] Step 4: Determine the optimal (correct) compensation mode based on the calibrated virtual array spectrum.

[0111] In practical applications, if the compensation is correct, the obtained virtual array is a sequence with a uniform phase difference. When performing FFT on it, the peak value of the obtained power spectrum is the highest; if the compensation is incorrect, there are residuals in the phase of the obtained virtual array, which is an array with a non-uniform phase difference, and the peak value of the power spectrum is relatively low. Therefore, the compensation mode corresponding to the array spectrum with the highest peak can be determined as the optimal (correct) compensation mode.

[0112] Step 5: Determine the speed and azimuth of the target according to the optimal (correct) compensation mode.

[0113] In practical applications, after correct compensation, performing FFT in the azimuth dimension can obtain azimuth angle information. Correspondingly, the speed corresponding to this compensation mode is the target speed. Therefore, the speed and azimuth solved based on the optimal (correct) compensation mode can be determined as the speed and azimuth of the finally obtained target.

[0114] However, the actual test results show that due to various factors such as noise disturbance and hardware errors, there will be a certain error ratio when using the above algorithm to resolve velocity ambiguity. For example, it is close to 10%, which may lead to incorrect selection of the compensation mode, and then lead to abnormal speeds and azimuths of each target point in the output target point cloud, resulting in low accuracy of target tracking.

[0115] Furthermore, since the MIMO compensation methods of the same target at different times (different frames) are independent and different, which shows that the speed of the same target is constantly changing over time, and the target azimuth jumps greatly, this will affect the target tracking, resulting in a decline in performance indicators such as target detection and false detection, especially in congested scenarios, the phenomenon is more significant.

[0116] In the actual process, the technical concept of this application is as follows: Since there are perturbations in the data itself, it is impossible to optimize single-frame data. The correlation between multiple frames in the time domain undoubtedly provides additional decision-making features for MIMO velocity ambiguity resolution. Specifically, after determining all compensation modes of the target point, the trajectory of the tracking target can be processed based on all compensation modes, that is, using the differential velocity of the trajectory to first correct the target observation value at the current moment and then perform association. This can greatly reduce the impact of MIMO radar ambiguity resolution errors on target tracking, thereby enabling the output of a trajectory with relatively accurate velocity and azimuth, reducing the performance loss caused by sudden changes in velocity and azimuth, and improving the accuracy of velocity tracking.

[0117] Based on the above analysis process, an embodiment of this application provides a target tracking method. By determining the initial trajectory of the tracking target, correcting the initial trajectory based on the differential velocity of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory, a corrected trajectory of the initial trajectory is obtained. Finally, the tracking target can be tracked according to the trajectory differential velocity of the corrected trajectory, thereby determining the actual running trajectory of the tracking target. In this technical solution, the radar performs trajectory correction and target tracking based on the differential velocity of the trajectory, can output accurate velocity and accurate azimuth information of the tracking target, improves the accuracy and reliability of tracking, and reduces the probability of target misdetection while enhancing target detection.

[0118] Next, the technical solution of this application will be described in detail through specific embodiments. It should be noted that these specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0119] Figure 3 FIG. 10 is a schematic flowchart of Embodiment 1 of the target tracking method provided by an embodiment of this application. This method is explained with a detection device as the execution subject, and the detection device can be a MIMO radar. As Figure 3 shown, the target tracking method may include the following steps:

[0120] S301. Determine the initial trajectory of the tracking target.

[0121] In this embodiment, when tracking a tracking target, it is first necessary to determine the initial trajectory of the tracking target. After confirming the initial trajectory, the tracking target can be processed for tracking.

[0122] Optionally, to determine the initial trajectory of the tracking target, first determine the starting point of the initial trajectory, and then perform neighborhood point association based on the speed information corresponding to the optimal compensation mode determined for this starting point, the assumed target acceleration, frame interval, etc. to obtain an initial trajectory of 2 points. Then, predict the change of the tracking target based on the speed, azimuth, and distance information of the second point in the initial trajectory, and perform association within the neighborhood of the predicted point to obtain an initial trajectory of 3 points, and so on, until the number of target points on the initial trajectory meets the quantity requirement. After confirming some conditions such as whether the smoothness of the initial trajectory meets the preset smoothness condition, the initial trajectory of the tracking target can be obtained. In practical applications, usually, an initial trajectory generally contains 4 target points to become a tracking trajectory.

[0123] Exemplarily, if the number of transmitting antennas of the detection device is equal to 3, at this time, the compensation modes (e.g., MIMO compensation mode) of each target point in the target point cloud of the tracking target at a certain moment include 3 types, namely MIMO compensation mode 1, MIMO compensation mode 2, and MIMO compensation mode 3. The speeds and azimuths are different under different MIMO compensation modes, and the distances are the same. For example, Figure 4 is the information of a single target point of the tracking target. Such as Figure 4 shown, assuming that the optimal compensation mode of a single target point is MIMO compensation mode 2, then MIMO compensation mode 1 and MIMO compensation mode 3 are the alternative compensation modes for this target point.

[0124] S302. Modify the initial trajectory based on the differential speed of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory to obtain the modified trajectory of the initial trajectory.

[0125] Optionally, after the initial trajectory of the tracking target is confirmed, the candidate compensation modes of each trajectory point in the initial trajectory can be re-determined based on the differential speed of the initial trajectory, and the optimal modification mode of this initial trajectory can be determined from the candidate compensation modes of each trajectory point. Then, the initial trajectory is modified based on this optimal modification mode to obtain the modified trajectory of the tracking target.

[0126] Among them, when the detection device determines the differential speed of the initial trajectory, it can compare the differential speed of this initial trajectory with the speeds corresponding to each candidate compensation mode of the trajectory point. If the speed error between the speed corresponding to a certain candidate compensation mode and the differential speed of this initial trajectory is the smallest, then this candidate compensation mode is determined as the optimal modification mode of the initial trajectory.

[0127] It can be understood that the optimal correction mode will be recognized as the optimal compensation mode for all the trajectory points on the initial trajectory of the tracking target. The speed information and azimuth information of all the trajectory points on the corrected trajectory will be output according to the speed information and azimuth information corresponding to the optimal correction mode.

[0128] S303. Track the tracking target according to the differential speed of the corrected trajectory, and determine the actual running trajectory of the tracking target.

[0129] In this embodiment, if the corrected trajectory meets the starting requirements, the corrected trajectory will be added to the tracker for tracking processing. Here, the starting requirements refer to that the number of trajectory points on the corrected trajectory meets the requirements, for example, the number of trajectory points is greater than or equal to 4, and the trajectory linearity is relatively good (that is, the smoothness of the trajectory meets the linear smoothing condition), etc.

[0130] In this step, the detection device can perform differential speed ambiguity resolution based on the differential speed of the corrected trajectory. That is, during the process of tracking the tracking target, the optimal compensation mode of the trajectory at the next moment is determined based on the differential speed of the trajectory at the current moment, and then according to the current information of each target point of the tracking target at the next moment, such as speed, distance, and azimuth information, etc., the trajectory points of the tracking target are associated using the optimal compensation mode, so as to determine the actual running trajectory of the tracking target.

[0131] The target tracking method provided in this embodiment determines the initial trajectory of the tracking target, corrects the initial trajectory based on the differential speed of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory, obtains the corrected trajectory of the initial trajectory, and tracks the tracking target according to the differential speed of the corrected trajectory to determine the actual running trajectory of the tracking target. In this technical solution, the radar performs trajectory correction and target tracking based on the differential speed of the trajectory, can output the accurate speed and accurate azimuth information of the tracking target, improves the accuracy and reliability of tracking, and while enhancing the target detection, reduces the probability of target misdetection.

[0132] Based on the above embodiment, Figure 5 is a schematic flowchart of the second embodiment of the target tracking method provided by the embodiment of the present application. As Figure 5 shown, the above S302 can be implemented through the following steps:

[0133] S501. Determine the differential speed of the initial trajectory.

[0134] In this embodiment, the differential speed can be obtained by dividing the radial displacement between the last trajectory point and the first trajectory point on the initial trajectory by the time interval between two adjacent trajectory points. Specifically, the time interval can be obtained by using the frame difference and frame rate between two adjacent trajectory points.

[0135] For example, when the initial trajectory has 4 trajectory points, the differential velocity of the initial trajectory can be calculated based on the radial displacement and time difference of the 4 trajectory points on the initial trajectory. The formula used is v = Δr / Δt, where the radial displacement Δr is the radial distance of trajectory point 4 minus the radial distance of trajectory point 1; the time difference Δt is the frame difference from trajectory point 1 to trajectory point 4 multiplied by the time interval between two adjacent frames.

[0136] S502. Determine the velocity error between the velocity corresponding to the candidate compensation mode of each trajectory point in the initial trajectory and the differential velocity of the initial trajectory.

[0137] In this embodiment, each trajectory point on the initial trajectory has multiple candidate compensation modes, and each candidate compensation mode corresponds to a velocity. For example, for a detection device with the number of transmitting antennas equal to 3, each trajectory point on its initial trajectory has 3 candidate compensation modes. Correspondingly, each trajectory point corresponds to three velocities.

[0138] Optionally, the velocities corresponding to each trajectory point can be compared with the differential velocity of the initial trajectory respectively to determine the velocity error between the velocities corresponding to each trajectory point and the differential velocity of the initial trajectory.

[0139] S503. Determine the candidate compensation mode corresponding to the velocity with the minimum velocity error as the optimal correction mode of the initial trajectory.

[0140] Optionally, after determining the velocity error between the velocities corresponding to each trajectory point and the differential velocity of the initial trajectory, the minimum velocity error can be determined therefrom, and then the velocity with the minimum velocity error and the candidate compensation mode corresponding to the velocity with the minimum velocity error can be determined. The candidate compensation mode corresponding to the velocity with the minimum velocity error can be determined as the optimal correction mode of the initial trajectory.

[0141] For example, for each trajectory point with 3 candidate compensation modes, if the candidate compensation mode corresponding to the velocity with the minimum velocity error is candidate compensation mode 3, then candidate compensation mode 3 is used as the optimal correction mode of the initial trajectory.

[0142] S504. Use the velocity information and azimuth information corresponding to the above optimal correction mode to correct the velocity information and azimuth information of each trajectory point in the initial trajectory, and obtain the corrected trajectory of the initial trajectory.

[0143] Exemplarily, when the optimal correction mode is determined, the information of all trajectory points on the initial trajectory is made to use the information of the optimal correction mode as the final output information, that is, the velocity information and azimuth information of each trajectory point in the corrected trajectory of the initial trajectory are the velocity information and azimuth information corresponding to the optimal correction mode.

[0144] In this embodiment, according to the differential velocity of the initial trajectory, the optimal compensation mode of each trajectory point on the initial track can be corrected to obtain the corrected velocity information and azimuth information, so as to output a corrected track with higher quality.

[0145] The target tracking method provided by the embodiment of the present application determines the differential velocity of the initial trajectory, determines the velocity error between the velocity corresponding to the candidate compensation mode of each trajectory point in the initial trajectory and the differential velocity of the initial trajectory, determines the candidate compensation mode corresponding to the velocity with the smallest velocity error as the optimal correction mode of the initial trajectory, and finally uses the velocity information and azimuth information corresponding to the optimal correction mode to correct the velocity information and azimuth information of each trajectory point in the initial trajectory to obtain the corrected trajectory of the initial trajectory. In this technical solution, the optimal correction mode is determined based on the differential velocity of the initial trajectory, and then the velocity information and azimuth information corresponding to the optimal correction mode are used for correction, so as to obtain a corrected trajectory with higher accuracy, thereby providing a prerequisite for obtaining an accurate tracking result subsequently.

[0146] Optionally, based on the above embodiments, Figure 6 is a schematic flowchart of the third embodiment of the target tracking method provided by the embodiment of the present application. As Figure 6 shown, the above S303 can be implemented through the following steps:

[0147] S601. Determine the optimal tracking compensation mode of the tracking target at the next moment according to the trajectory differential velocity of the corrected trajectory.

[0148] Exemplarily, in the process of target tracking, the obtaining method of the trajectory differential velocity of the corrected trajectory may be the same as or different from the obtaining method of the differential velocity of the initial trajectory. As an example, the trajectory differential velocity of the corrected trajectory can be determined according to the radial displacement between the first trajectory point and the last trajectory point on the corrected trajectory and the time difference between two adjacent trajectory points. As another example, the trajectory differential velocity of the corrected trajectory can be predicted based on the principle of Kalman filtering. Specifically, using the linear system state equation, the trajectory differential velocity of the corrected trajectory is predicted through the velocity information of each trajectory point on the corrected trajectory.

[0149] It can be understood that when determining the trajectory differential velocity of the corrected trajectory, in order to ensure the real-time nature of the velocity, the selected points must be the latest multiple target points on the current corrected trajectory.

[0150] Based on the trajectory differential velocity and the velocities corresponding to various candidate compensation modes, the optimal tracking compensation mode of the tracking target at the next moment can be determined, that is, the candidate compensation mode corresponding to the velocity with the smallest velocity error is determined as the optimal compensation mode at the next moment (for example, the optimal compensation mode is "mode x").

[0151] S602. Determine the target trajectory point of the tracking target at the next moment based on the speed information and azimuth information corresponding to the optimal tracking compensation mode.

[0152] In this embodiment, when the detection device performs target detection, it can obtain the detection data of the tracking target at each moment. The detection data at each detection moment includes multiple frames of data. Each frame of data in the detection data contains the information of multiple target points at the corresponding moment, generally including information such as speed, distance, and azimuth. Therefore, when tracking the tracking target, the target trajectory point that can be successfully associated at the next moment can be determined among the multiple target points of the tracking target at the next moment according to the speed information and azimuth information corresponding to the optimal tracking compensation mode.

[0153] S603. Use the speed information and azimuth information corresponding to the optimal tracking compensation mode to correct the speed information and azimuth information of the target trajectory point.

[0154] In practical applications, since each target point has an optimal compensation mode, that is, it has optimal speed information and azimuth information. When determining the target trajectory point of the tracking target at the next moment, in order to make the output information of the target trajectory point accurate, the speed information and azimuth information of the target trajectory point can be corrected by using the speed information and azimuth information corresponding to the optimal tracking compensation mode, that is, the information of the target trajectory point is output according to the speed information and azimuth information corresponding to the optimal tracking compensation mode.

[0155] S604. Use the speed information and azimuth information of the corrected target trajectory point to update the trajectory of the tracking target, and obtain the actual running trajectory of the tracking target.

[0156] Optionally, after determining the output information of the target trajectory point, the trajectory of the tracking target can be continued, so as to obtain the actual running trajectory of the tracking target.

[0157] In this step, when performing target tracking, correct the optimal compensation mode of the target trajectory point, and obtain the corrected speed and azimuth, so that the output actual running trajectory is smoother and the output speed information and azimuth information are more accurate, which can effectively avoid problems such as trajectory mis-association and premature disappearance.

[0158] The target tracking method provided by the embodiments of the present application determines the optimal tracking compensation mode of the tracking target at the next moment according to the trajectory differential velocity of the corrected trajectory, determines the target trajectory point of the tracking target at the next moment based on the velocity information and azimuth information corresponding to the optimal tracking compensation mode, corrects the velocity information and azimuth information of the target trajectory point by using the velocity information and azimuth information corresponding to the optimal tracking compensation mode, and finally updates the trajectory of the tracking target by using the velocity information and azimuth information of the corrected target trajectory point to obtain the actual running trajectory of the tracking target. In this technical solution, the trajectory of the tracking target is tracked based on the trajectory differential velocity, and the velocity information and azimuth information corresponding to the optimal compensation mode are output, so that a trajectory with more accurate and reliable velocity information and azimuth information can be obtained, greatly reducing the performance loss caused by the sudden change of the velocity and azimuth of the tracking target, improving the target detection rate while reducing the probability of target misdetection, and its performance is more remarkable in the target congestion scenario.

[0159] Based on the above embodiments, Figure 7 It is a schematic flowchart of the fourth embodiment of the target tracking method provided by the embodiments of the present application. As Figure 7 shown, the above S301 can be implemented through the following steps:

[0160] S701. Determine the trajectory starting point of the tracking target.

[0161] In this embodiment, when determining the initial trajectory of the tracking target, a trajectory point needs to be first determined as the starting point of the initial trajectory. Exemplarily, a target point can be randomly selected from the target point cloud corresponding to the initial moment as the trajectory starting point, or other strategies can be used to select the trajectory starting point. The embodiments of the present application do not limit the method for determining the trajectory starting point.

[0162] S702. Determine the target points of the same target at different times that match the trajectory starting point as trajectory points.

[0163] Exemplarily, neighborhood point association is performed based on the velocity information, azimuth information corresponding to the optimal compensation mode determined for the trajectory starting point, and the frame interval information of the tracking target, and the second trajectory point that matches the trajectory starting point and the third trajectory point that matches the second trajectory point are sequentially determined until a preset number of trajectory points are determined.

[0164] In this embodiment, the initial trajectory is determined by trajectory association based on the optimal compensation mode determined for the trajectory starting point. For example, if the optimal compensation mode determined for the trajectory starting point is candidate compensation mode 1, then when other trajectory points are associated with it, the speed and azimuth corresponding to candidate compensation mode 1 must also be used to associate and match with the trajectory starting point. This logic is based on the following assumption: for the same tracking target at different times, the azimuth deviation corresponding to the same candidate compensation mode is not large and it is easier to associate, while the azimuth deviation corresponding to different candidate compensation modes is large and it is difficult to associate.

[0165] Exemplarily, for the determined trajectory starting point, neighborhood point association is performed according to the speed of this trajectory starting point, the acceleration range of the assumed tracking target, the frame interval and other information to determine the second trajectory point. Then, based on the speed, azimuth and distance information of the trajectory starting point and the second trajectory point, prediction is performed within the neighborhood of the second trajectory point, and association is performed within the neighborhood of the predicted point to obtain the third trajectory point, and so on until the number of determined trajectory points meets the quantity requirement of the initial trajectory.

[0166] It can be understood that the determination of all trajectory points on the initial trajectory requires the association of associated points according to the speed information and azimuth information corresponding to the last compensation mode determined for the trajectory starting point. For example, Figure 8 Schematic diagram of the association for the trajectory starting point. As Figure 8 shown, the candidate compensation modes of target point 1 and target point 2 include: MIMO compensation mode 1, MIMO compensation mode 2 and MIMO compensation mode 3, and each candidate compensation mode has corresponding speed, azimuth and distance information.

[0167] Exemplarily, in Figure 8 the schematic diagram shown, if the optimal compensation mode of the trajectory starting point of the initial trajectory (for example, Figure 8 target point 1 in) is MIMO compensation mode 2, then all target trajectory points (for example, target point 2) associated with this trajectory starting point need to use the information of MIMO compensation mode 2 to judge whether this target trajectory point can be successfully associated with the trajectory starting point. For example, although the optimal compensation mode of target point 2 is MIMO compensation mode 1, it also needs to use the information of MIMO compensation mode 2 to judge whether it can be associated with the trajectory starting point successfully until a preset number of trajectory points are determined.

[0168] Exemplarily, Figure 9 Schematic diagram of generating an initial trajectory based on the optimal compensation mode of the trajectory starting point. As Figure 9As shown, each of the trajectory points 1 to 4 has 3 candidate compensation modes, namely MIMO compensation mode 1, MIMO compensation mode 2, and MIMO compensation mode 3. Each candidate compensation mode has corresponding speed information, azimuth information, and distance information. Among them, the optimal compensation mode for trajectory point 1 is MIMO compensation mode 2, the optimal compensation mode for trajectory point 2 is MIMO compensation mode 1, the optimal compensation mode for trajectory point 3 is MIMO compensation mode 2, and the optimal compensation mode for trajectory point 4 is MIMO compensation mode 3.

[0169] During Figure 9 the confirmation of the trajectory points on the initial trajectory, each of the trajectory points 1 to 4 needs to determine whether the trajectory points 2 to 4 are correlated and matched according to the optimal compensation mode of trajectory point 1, that is, MIMO compensation mode 2.

[0170] S703. Generate an initial trajectory of the tracking target according to the above trajectory starting point and the determined preset number of trajectory points.

[0171] Among them, the number of trajectory points on the initial trajectory meets the quantity requirements, and the initial trajectory meets the preset smoothness conditions.

[0172] In this embodiment, when the number of determined trajectory points meets the quantity requirements of the initial trajectory (for example, meets the length requirement of 4 points), connect the above multiple trajectory points in the determined order of the trajectory points to generate a trajectory, and then determine whether the trajectory meets the preset smoothness conditions. After the trajectory passes the confirmation of the above two conditions or other logical conditions, the initial trajectory of the tracking target is formed, and the initial trajectory can be added to the tracking trajectory list.

[0173] The target tracking method provided by the embodiment of the present application determines the trajectory starting point of the tracking target, determines the target points of the same target at different times that match the trajectory starting point as trajectory points, generates an initial trajectory of the tracking target according to the trajectory starting point and the determined preset number of trajectory points, and the number of trajectory points on the initial trajectory meets the quantity requirements, and the initial trajectory meets the preset smoothness conditions. In this technical solution, based on the trajectory starting point, the target points of the tracking target at different times that match the trajectory starting point are used as trajectory points, and then the initial trajectory is generated, which lays a foundation for the subsequent correction of the trajectory.

[0174] Based on the above embodiments, before determining the initial trajectory of the tracking target, the detection device can also cluster the target point cloud of the tracking target at the same moment based on the determined candidate compensation modes to obtain the target clustering results corresponding to each candidate compensation mode, and the target clustering results include the speed information and azimuth information corresponding to the candidate compensation modes.

[0175] Optionally, cluster the target point clouds of the tracking target at the same moment according to the determined candidate compensation modes respectively, and divide the target points with the same optimal compensation mode into the same set, so as to obtain the target clustering results corresponding to each optimal compensation mode.

[0176] In this step, the detection device can adopt a general clustering algorithm to cluster the target point clouds of the tracking target at the same moment according to each determined candidate compensation mode, so as to obtain the speed information and azimuth information of the tracking target under different candidate compensation modes.

[0177] For example, when the candidate compensation modes of the tracking target include candidate compensation mode 0, candidate compensation mode 1, and candidate compensation mode 2, first cluster the target point clouds of the tracking target at the first moment according to candidate compensation mode 0 to obtain the target clustering result of candidate compensation mode 0, then cluster the target point clouds of the tracking target at the first moment according to candidate compensation mode 1 to obtain the target clustering result of candidate compensation mode 1, and finally cluster the target point clouds of the tracking target at the first moment according to candidate compensation mode 2 to obtain the target clustering result of candidate compensation mode 2, so as to obtain the target clustering results of all candidate compensation modes, that is, the speed information and azimuth information of each candidate compensation mode.

[0178] In this embodiment, the detection device clusters the target point clouds of the tracking target at the same moment according to the determined candidate compensation modes respectively. In addition to obtaining the target clustering results under the optimal compensation mode, it can also obtain the target clustering results under the remaining candidate compensation modes, and use the target clustering results under the remaining candidate compensation modes as the tracking module alternative set, laying a foundation for the subsequent implementation of target tracking.

[0179] Optionally, in this embodiment, before the detection device clusters the target point clouds of the tracking target at the same moment according to the determined candidate compensation modes respectively to obtain the target clustering results corresponding to each candidate compensation mode, it can first determine the candidate compensation modes. Exemplarily, Figure 10 This is the flowchart of Embodiment 5 of the target tracking method provided by the embodiment of the present application. As Figure 10 shown, the method may further include the following steps:

[0180] S1001. Obtain multiple frames of radar signals of the tracking target, and respectively determine the power diagrams of each frame of radar signals.

[0181] In this embodiment, the detection device can first preprocess the echo signal output by the detection device to obtain the discrete digital signal of the detection device, then perform two-dimensional Fourier transform processing on the above discrete digital signal to obtain the frequency domain data of the discrete digital signal, and then perform non-coherent accumulation processing on the frequency domain data of the discrete digital signal to obtain the power diagram of the echo signal.

[0182] Exemplarily, assume that the echo signal transmitted by the m-th transmitting antenna and received by the n-th receiving antenna within the i-th period of the detection device is s mn (i, t), where 1 ≤ i ≤ I, 1 ≤ m ≤ M, 1 ≤ n ≤ N, t represents the fast time within the i-th period, I represents the number of transmitting periods, M is the number of transmitting antennas, and N is the number of receiving antennas. The echo signal s mn (i, t) is subjected to down-conversion processing to become an intermediate-frequency signal. After passing through intermediate-frequency filtering, amplification and other processing, it is sampled by an ADC and converted into a discrete digital signal s mn (i, k), where k is the ADC sampling sequence number at a certain sampling rate.

[0183] Optionally, the discrete digital signal of the detection device is also the data of each channel of the virtual antenna array possessed by the detection device. The detection device performs two-dimensional FFT processing on the above discrete digital signal to obtain the frequency-domain data of the discrete digital signal.

[0184] Specifically, the discrete digital signal s mn (i, k) is subjected to a one-dimensional N r -point FFT transformation along the k direction, and the data obtained after the one-dimensional FFT transformation is then subjected to a two-dimensional N d -point FFT transformation along the i-th period direction. The frequency-domain data obtained after the two-dimensional FFT is denoted as s mn (n d , n r ), where n d , n r represents the sequence number after the two-dimensional FFT, and 0 ≤ n r < N r , 0 ≤ n d < N d , s mn (n d , n r ) can be briefly denoted as s mn . In practical applications, N d is usually equal to I and is a power of 2.

[0185] The frequency-domain data s mn of the above discrete digital signal is arranged as follows according to the spatial and temporal order of the transmitting and receiving antennas:

[0186] S mn = [S 11 , S 12 ,... S 1N , S 21 , S 22 ,... S 2N …, SM1 , S M2 ,... S MN

[0187] To maximize the detection signal-to-noise ratio, the arranged discrete digital signals can be processed by non-coherent integration to obtain the power map of the echo signal. Optionally, the process of non-coherent integration can be expressed by the following formula:

[0188]

[0189] S int is an N d × N r data matrix.

[0190] S1002. Determine the target points of the tracking target at different times according to the power maps of the radar signals of each frame.

[0191] In this step, a constant false-alarm rate (CFAR) detection module can be deployed in the detection device. Therefore, after obtaining the power maps of the radar signals of each frame, the detection device can input them into the CFAR detection module respectively. Under the condition of maintaining a constant false-alarm rate, the multi-frame radar signals and noise of the tracking target are discriminated to determine whether the tracking target exists in the radar signals of each frame, so as to obtain the target points of the tracking target at different times.

[0192] Optionally, after processing the noise in the power map, the CFAR detection module can determine a threshold and compare this threshold with each signal point in the power map. If the radar signals of each frame exceed this threshold, it is determined that the tracking target exists; otherwise, it is determined that the tracking target does not exist.

[0193] Exemplarily, assume that the power maps of the radar signals of each frame are represented by the S int matrix. After performing constant false-alarm detection on the S int matrix, for example, at a certain moment, a total of P target points of the tracking target are detected, and their two-dimensional index numbers are recorded as (d p , r p ), where 1 ≤ p ≤ P, d p represents the Doppler index number of the p-th target point, and r p represents the distance index number of the p-th target point.

[0194] S1003. According to the time sequence of the radar signals of each frame, perform trajectory association on the target points of the tracking target at different times to determine the estimated motion speed and estimated motion direction of the tracking target.

[0195] ​In this embodiment, a target tracking algorithm in related technologies can be used to track a tracking target, and then the target points at different times are traced to obtain the estimated motion speed and estimated motion direction of each object.

[0196] Exemplarily, each frame of radar signal is processed according to the time sequence of each frame of radar signal to determine the target point of each frame of radar signal, that is, the target points of the tracking target at different times. For example, for the P target points in S1002 above, through r p the estimated distance information of the tracking target can be calculated, and through d p the estimated motion speed of the tracking target can be calculated. For the target points of the tracking target at different times, by extracting the data of each channel after FFT in the virtual antenna array of the detection device for one-dimensional FFT processing, the estimated motion direction of the tracking target can be obtained.

[0197] S1004. According to the estimated motion speed and estimated motion direction of the tracking target, a candidate compensation mode is selected from a plurality of preset compensation modes.

[0198] Optionally, a plurality of compensation modes preset for the tracking target can be determined according to the properties of the power diagram. Optionally, the plurality of preset compensation modes may include a plurality of MIMO compensation modes. The MIMO compensation modes that do not meet the constraint conditions such as the estimated motion speed and estimated motion direction of the tracking target are excluded from the plurality of MIMO compensation modes, so as to determine the remaining MIMO compensation modes in the plurality of preset compensation modes as candidate compensation modes.

[0199] S1005. According to the virtual array spectra under each compensation mode in the candidate compensation mode, an optimal compensation mode is determined.

[0200] In one possible implementation, this S1005 can be implemented through the following steps:

[0201] A1. Using each compensation mode of the candidate compensation mode, the virtual array vector of the detection device is compensated and corrected to obtain the corrected virtual array vector under each compensation mode.

[0202] In this embodiment, by using each compensation mode of the candidate compensation mode to compensate and correct the virtual array vector of the detection device respectively, the corrected virtual array vector S under different compensation modes can be obtained c . For example, MIMO compensation mode 0 corresponds to the corrected virtual array vector S c0 , MIMO compensation mode 1 corresponds to the corrected virtual array vector S c1 , MIMO compensation mode 2 corresponds to the corrected virtual array vector S c2 .

[0203] A2. Perform Fourier transform on the calibrated virtual array vectors under each compensation mode to obtain the virtual array spectra under each compensation mode.

[0204] Optionally, when using the MIMO deambiguation algorithm for processing, performing azimuth FFT on the calibrated virtual array vectors under each compensation mode respectively can obtain the virtual array spectra under each compensation mode.

[0205] A3. According to the virtual array spectra under each compensation mode, determine the compensation mode with the highest peak value of the virtual array spectrum as the optimal compensation mode.

[0206] In practical applications, if the compensation is correct, the obtained virtual array is a sequence with a uniform phase difference. When performing FFT on it, the peak value of the obtained virtual array spectrum is the highest; if the compensation is incorrect, there are residuals in the phase of the obtained virtual array, which is an array with a non-uniform phase difference. When performing FFT on it, the peak value of the obtained virtual array spectrum is relatively low. Based on the above principle, the compensation mode with the highest peak value of the virtual array spectrum can be determined as the optimal compensation mode.

[0207] The target tracking method provided by the embodiments of the present application obtains multiple frames of radar signals of the tracking target, respectively determines the power maps of each frame of radar signals, determines the target points of the tracking target at different times according to the power maps of each frame of radar signals, associates the target points of the tracking target at different times according to the time sequence of each frame of radar signals, determines the estimated movement speed and estimated movement direction of the tracking target, screens out candidate compensation modes from a preset plurality of compensation modes according to the estimated movement speed and estimated movement direction of the tracking target, and determines the optimal compensation mode based on the virtual array spectra under each compensation mode in the candidate compensation modes. In this technical solution, by determining the candidate compensation mode and the optimal compensation mode, a foundation is laid for subsequent target tracking.

[0208] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0209] Figure 11 It is a schematic structural diagram of an embodiment of the target tracking device provided by the embodiments of the present application. As Figure 11 shown, the target tracking device may include:

[0210] A determination module 1101, configured to determine the initial trajectory of the tracking target;

[0211] A processing module 1102, configured to correct the initial trajectory based on the differential speed of the initial trajectory and the candidate compensation modes of each trajectory point in the initial trajectory to obtain the corrected trajectory of the initial trajectory;

[0212] The tracking module 1103 is configured to track the tracking target according to the trajectory differential velocity of the corrected trajectory, and determine the actual running trajectory of the tracking target.

[0213] In a possible design of the embodiment of the present application, the processing module 1102 is specifically configured to:

[0214] Determine the velocity error between the velocity corresponding to the candidate compensation mode of each trajectory point in the initial trajectory and the differential velocity of the initial trajectory;

[0215] Determine the candidate compensation mode corresponding to the velocity with the smallest velocity error as the optimal correction mode of the initial trajectory;

[0216] Use the velocity information and azimuth information corresponding to the optimal correction mode to correct the velocity information and azimuth information of each trajectory point in the initial trajectory, and obtain the corrected trajectory of the initial trajectory.

[0217] Optionally, the tracking module 1103 is specifically configured to:

[0218] Determine the optimal tracking compensation mode of the tracking target at the next moment according to the trajectory differential velocity of the corrected trajectory;

[0219] Based on the velocity information and azimuth information corresponding to the optimal tracking compensation mode, determine the target trajectory point of the tracking target at the next moment;

[0220] Use the velocity information and azimuth information corresponding to the optimal tracking compensation mode to correct the velocity information and azimuth information of the target trajectory point;

[0221] Use the velocity information and azimuth information of the corrected target trajectory point to update the trajectory of the tracking target, and obtain the actual running trajectory of the tracking target.

[0222] In another possible design of the embodiment of the present application, the determining module 1101 is specifically configured to:

[0223] Determine the trajectory starting point of the tracking target;

[0224] Determine the target points of the same target at different times that match the trajectory starting point as trajectory points;

[0225] Generate the initial trajectory of the tracking target according to the trajectory starting point and the determined preset number of trajectory points, where the number of trajectory points on the initial trajectory meets the quantity requirement, and the initial trajectory meets the preset smooth condition.

[0226] Optionally, the determining module 1101 is configured to determine the target points of the same target at different times that match the trajectory starting point as trajectory points, specifically:

[0227] The determining module 1101 is specifically configured to perform neighborhood point association based on the speed information, azimuth information corresponding to the optimal compensation mode determined for the trajectory starting point, and the frame interval information of the tracking target, and sequentially determine a second trajectory point matching the trajectory starting point and a third trajectory point matching the second trajectory point until a preset number of trajectory points are determined.

[0228] In another possible design of the embodiment of the present application, the processing module 1102 is further configured to, before the determining module 1101 determines the initial trajectory of the tracking target, cluster the target point clouds of the tracking target at the same moment according to the determined candidate compensation modes, and obtain a target clustering result corresponding to each candidate compensation mode, where the target clustering result includes the speed information and azimuth information corresponding to the candidate compensation mode.

[0229] Optionally, the processing module 1102 is further configured to perform the following steps before clustering the target point clouds of the tracking target at the same moment according to the determined candidate compensation modes to obtain a target clustering result corresponding to each candidate compensation mode:

[0230] Obtain multiple frames of radar signals of the tracking target, and respectively determine the power maps of each frame of radar signals;

[0231] According to the power maps of each frame of radar signals, determine the target points of the tracking target at different moments;

[0232] Perform trajectory association on the target points of the tracking target at different moments according to the time sequence of each frame of radar signals, and determine the estimated motion speed and estimated motion direction of the tracking target;

[0233] Screen out candidate compensation modes from a preset plurality of compensation modes according to the estimated motion speed and estimated motion direction of the tracking target;

[0234] Determine the optimal compensation mode according to the virtual array spectra under each compensation mode in the candidate compensation modes.

[0235] The device provided in the embodiment of the present application can be used to execute the technical solutions described in the above method embodiments, and its implementation principles and technical effects are similar, and will not be elaborated here.

[0236] It should be noted that it should be understood that the division of each module of the above device is only a division of logical functions. In actual implementation, it can be fully or partially integrated into a physical entity, or physically separated. And these modules can all be implemented in the form of software called by a processing element; they can also all be implemented in hardware; they can also be partially implemented in the form of software called by a processing element and partially implemented in hardware. For example, the determination module can be a separately established processing element, or can be integrated in a certain chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and the function of the above determination module can be called and executed by a certain processing element of the above device. The implementation of other modules is similar. In addition, all or part of these modules can be integrated together or can be independently implemented. The processing element mentioned here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed by the hardware integrated logic circuit or software-form instructions in the processor element.

[0237] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center to another website, computer, server or data center in a wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server, data center, etc. that contains one or more integrated available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)).

[0238] Figure 12 It is a schematic structural diagram of the detection device provided by the embodiment of the present application. The detection device can be a device such as a MIMO radar. As Figure 12As shown, the detection device may include: a processor 1201, a memory 1202, a transceiver 1203, and a system bus 1204. Among them, the memory 1202 and the transceiver 1203 are connected to the processor 1201 through the system bus 1204 and complete communication with each other. The memory 1202 is used to store computer-executable instructions, and the transceiver 1203 is used to communicate with other devices. When the processor 1201 executes the above computer-executable instructions, the technical solutions of the above method embodiments are implemented.

[0239] The Figure 12 The system bus mentioned above may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity, only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus. The communication interface is used to implement communication between the database access device and other devices (such as clients, read-write libraries, and read-only libraries). The memory may include Random Access Memory (RAM), and may also include non-volatile memory, such as at least one disk memory.

[0240] The above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0241] Optionally, an embodiment of the present application further provides a computer-readable storage medium. Computer-executable instructions are stored in the computer-readable storage medium. When it runs on a computer, the computer is enabled to execute the technical solutions described in the above method embodiments.

[0242] Optionally, an embodiment of the present application further provides a chip for running instructions. The chip is used to execute the technical solutions described in the above method embodiments.

[0243] An embodiment of the present application further provides a computer program product. The computer program product includes a computer program. When the computer program is executed by a processor, the technical solutions described in the above method embodiments can be implemented.

[0244] In this application, "at least one" means one or more, and "multiple" means two or more. "And / or" describes the relationship between associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after; in a formula, the character " / " represents a "division" relationship between the associated objects before and after. "At least one of the following" or a similar expression refers to any combination of these items, including any combination of single items or plural items.

[0245] It can be understood that the various numerical numbers involved in the embodiments of this application are only for the convenience of description and are not used to limit the scope of the embodiments of this application. In the embodiments of this application, the magnitudes of the serial numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic and should not constitute any limitation to the implementation process of the embodiments of this application.

[0246] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A target tracking method, characterized in that: include: Determining an initial trajectory of a tracked target, wherein the initial trajectory includes a plurality of trajectory points; Correcting the initial trajectory based on a differential velocity of the initial trajectory and a candidate compensation mode for each trajectory point in the initial trajectory to obtain a corrected trajectory of the initial trajectory; the differential velocity is obtained by dividing the radial displacement between the last trajectory point and the first trajectory point on the initial trajectory by the time interval between two adjacent trajectory points; The candidate compensation mode is a mode suitable for target speed compensation selected from a plurality of preset compensation modes according to the estimated motion speed and estimated motion direction of the tracked target; The tracking target is tracked according to the trajectory differential speed of the corrected trajectory to determine the actual running trajectory of the tracking target.

2. The method according to claim 1, characterized in that The correcting the initial trajectory based on the differential velocity of the initial trajectory and the candidate compensation mode of each trajectory point in the initial trajectory to obtain a corrected trajectory of the initial trajectory includes: determining a differential velocity of the initial trajectory; determining a velocity error between a velocity corresponding to a candidate compensation mode for each trajectory point in the initial trajectory and a differential velocity of the initial trajectory; Selecting, from the candidate compensation modes of all trajectory points, a candidate compensation mode corresponding to a speed with a minimum speed error as the optimal correction mode of the initial trajectory; The speed information and the orientation information corresponding to the optimal correction mode are used to correct the speed information and the orientation information of each trajectory point in the initial trajectory to obtain a corrected trajectory of the initial trajectory.

3. The method according to claim 2, characterized in that Tracking the target according to the trajectory differential speed of the corrected trajectory to determine the actual running trajectory of the target includes: determining an optimal tracking compensation mode of the tracking target at a next moment according to the trajectory differential velocity of the corrected trajectory; Determining a target trajectory point of the tracked target at a next moment based on the speed information and the azimuth information corresponding to the optimal tracking compensation mode; Correcting the speed information and the orientation information of the target track point using the speed information and the orientation information corresponding to the optimal tracking compensation mode; The trajectory of the tracked target is updated using the corrected speed information and orientation information of the target trajectory point to obtain the actual running trajectory of the tracked target.

4. The method according to claim 1, wherein Determining the initial trajectory of the tracking target includes: Determining a trajectory starting point of the tracked target; Determine a target point of the same target at a different time that matches the starting point of the trajectory as a trajectory point; An initial trajectory of the tracked target is generated according to the trajectory starting point and the determined preset number of trajectory points, the number of trajectory points on the initial trajectory meets a quantity requirement, and the initial trajectory meets a preset smoothness condition.

5. The method according to claim 4, characterized in that The determining of target points of the same target at different times that match the trajectory starting point as trajectory points includes: Based on the speed information, orientation information corresponding to the optimal compensation mode determined for the starting point of the trajectory and the frame interval information of the tracking target, neighborhood point association is performed, and a second trajectory point matching the starting point of the trajectory and a third trajectory point matching the second trajectory point are determined in sequence until a preset number of trajectory points are determined.

6. The method according to any one of claims 1 to 5, characterized in that Before determining the initial trajectory of the tracking target, the method further includes: The target point clouds of the tracked target at the same time are clustered according to the determined candidate compensation modes to obtain target clustering results corresponding to each candidate compensation mode, wherein the target clustering results include speed information and orientation information corresponding to the candidate compensation mode.

7. The method according to claim 6, characterized in that Before clustering the target point clouds of the tracked target at the same time according to the determined candidate compensation modes to obtain target clustering results corresponding to each candidate compensation mode, the method further includes: Acquire multiple frames of radar signals of the tracked target and determine a power graph of each frame of radar signals; Determining the target points of the tracked target at different times according to the power graph of each frame of radar signal; According to the time sequence of each frame of radar signal, the track points of the tracked target at different times are correlated to determine the estimated movement speed and estimated movement direction of the tracked target; Selecting a candidate compensation mode from a plurality of preset compensation modes according to the estimated movement speed and the estimated movement direction of the tracked target; An optimal compensation mode is determined according to the virtual array spectrum under each compensation mode among the candidate compensation modes.

8. A target tracking device, characterized in that: include: A determination module, configured to determine an initial trajectory of a tracked target, wherein the initial trajectory includes a plurality of trajectory points; a processing module, configured to correct the initial trajectory based on a differential velocity of the initial trajectory and a candidate compensation mode for each trajectory point in the initial trajectory, to obtain a corrected trajectory of the initial trajectory; the differential velocity is obtained by dividing the radial displacement between the last trajectory point and the first trajectory point on the initial trajectory by the time interval between two adjacent trajectory points; The candidate compensation mode is a mode suitable for target speed compensation selected from a plurality of preset compensation modes according to the estimated motion speed and estimated motion direction of the tracked target; The tracking module is used to track the tracking target according to the trajectory differential speed of the corrected trajectory to determine the actual running trajectory of the tracking target.

9. The device according to claim 8, characterized in that The processing module is specifically used to: determining a differential velocity of the initial trajectory; determining a velocity error between a velocity corresponding to a candidate compensation mode for each trajectory point in the initial trajectory and a differential velocity of the initial trajectory; Selecting, from the candidate compensation modes of all trajectory points, a candidate compensation mode corresponding to a speed with a minimum speed error as the optimal correction mode of the initial trajectory; The speed information and the orientation information corresponding to the optimal correction mode are used to correct the speed information and the orientation information of each trajectory point in the initial trajectory to obtain a corrected trajectory of the initial trajectory.

10. The device according to claim 9, characterized in that The tracking module is specifically used to: determining an optimal tracking compensation mode of the tracking target at a next moment according to the trajectory differential velocity of the corrected trajectory; Determining a target trajectory point of the tracked target at a next moment based on the speed information and the azimuth information corresponding to the optimal tracking compensation mode; Correcting the speed information and the orientation information of the target track point using the speed information and the orientation information corresponding to the optimal tracking compensation mode; The trajectory of the tracked target is updated using the corrected speed information and orientation information of the target trajectory point to obtain the actual running trajectory of the tracked target.

11. The device according to claim 8, characterized in that The determining module is specifically configured to: Determining a trajectory starting point of the tracked target; Determine a target point of the same target at a different time that matches the starting point of the trajectory as a trajectory point; An initial trajectory of the tracked target is generated according to the trajectory starting point and the determined preset number of trajectory points, the number of trajectory points on the initial trajectory meets a quantity requirement, and the initial trajectory meets a preset smoothness condition.

12. The device according to claim 11, characterized in that The determining module is used to determine the target point of the same target at different time points that matches the starting point of the trajectory as the trajectory point, specifically: The determination module is specifically configured to associate neighborhood points based on the speed information, orientation information corresponding to the optimal compensation mode determined for the trajectory starting point and the frame interval information of the tracking target, and sequentially determine a second trajectory point matching the trajectory starting point and a third trajectory point matching the second trajectory point, until a preset number of trajectory points are determined.

13. The device according to any one of claims 8 to 12, characterized in that The processing module is further configured to cluster the target point clouds of the tracked target at the same time according to the determined candidate compensation modes before the determination module determines the initial trajectory of the tracked target, to obtain target clustering results corresponding to each candidate compensation mode, wherein the target clustering results include speed information and orientation information corresponding to the candidate compensation mode.

14. The device according to claim 13, characterized in that The processing module is further configured to perform the following steps before clustering the target point clouds of the tracked target at the same time according to the determined candidate compensation modes and obtaining the target clustering results corresponding to each candidate compensation mode: Acquire multiple frames of radar signals of the tracked target and determine a power graph of each frame of radar signals; Determining the target points of the tracked target at different times according to the power graph of each frame of radar signal; According to the time sequence of each frame of radar signal, the track points of the tracked target at different times are correlated to determine the estimated movement speed and estimated movement direction of the tracked target; Selecting a candidate compensation mode from a plurality of preset compensation modes according to the estimated movement speed and the estimated movement direction of the tracked target; An optimal compensation mode is determined according to the virtual array spectrum under each compensation mode among the candidate compensation modes.

15. A detection device comprising: A processor, a memory, a transceiver, and computer program instructions stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program instructions.

16. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method according to any one of claims 1 to 7.

17. A computer program product comprising: A computer program, characterized in that when the computer program is executed by a processor, it is used to implement the method according to any one of claims 1 to 7.

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