CN115825912B - Radar signal processing method, device and storage medium - Google Patents
Radar signal processing method, device and storage medium Download PDFInfo
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Abstract
The application discloses a radar signal processing method, a radar signal processing device and a storage medium, which comprise the steps of acquiring frame data, preprocessing the frame data, and taking a trace point falling into an associated gate as a target value; taking the target value as the first track point of the track, sequentially establishing a track ID, and comparing all measured values in the later frame of data with the measured values of the established track ID until the track is stably started; configuring a track evaluation index for the track of which the track ID is established in the track initial stage so that newly received point track data is associated with the track according to the track evaluation index; and filtering the trace point data successfully associated with the track to perform filtering estimation on the latest state of the track. According to the method and the device, the radar can track single and multiple targets with high precision, the distance is not limited, the problem that target data at a far position are not concentrated is solved, and the accuracy rate of correlation between the target track and the track at a far position is improved.
Description
Technical Field
The application belongs to the technical field of radar data processing, and particularly relates to a radar signal processing method, a radar signal processing device and a storage medium.
Background
The echo signals received by the radar can detect the target through the signal processing system, but the spatial position, radial distance, speed and other motion parameters of the target are subjected to correlation matching, tracking filtering, estimation prediction and the like to effectively reduce environmental noise, the related motion parameters of the target in a detection area are estimated, the position of the target at the next moment is predicted, and a stable target track is formed. Under the condition of more clutter, the algorithm in the prior art is easy to generate track association errors, and can not solve the problems that the number of targets is not fixed, the targets with a longer distance are not concentrated and the like in the process of tracking the traffic radar targets. In the prior art, introducing characteristic information such as information entropy can obviously increase information dimension, or too coarse data importing steps are adopted, so that calculation cost is too high.
Disclosure of Invention
The invention aims to: the application provides a radar signal processing method, which aims to solve the technical problems that the track association is wrong, the number of targets is not fixed in the radar target tracking process, and targets with far distances are not concentrated; another object of the present application is to provide an electronic device, configured to implement the above-mentioned processing method; another object of the present application is to provide a storage medium storing a computer program for implementing the above processing method.
The technical scheme is as follows: the embodiment of the application provides a radar signal processing method, which comprises the following steps:
acquiring frame data, preprocessing the frame data, and taking a point trace falling into an association gate as a target value;
taking the target value as the first track point of the track, sequentially establishing a track ID, and comparing all measured values in the later frame of data with the measured values of the established track ID until the track is stably started;
configuring a track evaluation index for a track of which the track ID is established in a track initial stage so that newly received point track data is associated with the track according to the track evaluation index;
and filtering the trace point data successfully associated with the track to perform filtering estimation on the latest state of the track.
In some embodiments, the step of preprocessing the frame data comprises:
detecting the integrity degree of the data format of the frame header in the frame data, and filtering out the frame data with incomplete data format; and/or the number of the groups of groups,
judging the position relation between the frame data and the association gate, and filtering the frame data which does not fall into the association gate.
In some embodiments, the step of comparing all measurements in the subsequent frame of data with measurements for which the track ID has been established until the onset of track stabilization includes:
firstly, acquiring a radial distance difference delta d between a measured value in the data of the next frame and a measured value of the established track ID; when Δd < d m When the two measured values belong to the same track ID, judging that the two measured values belong to the same track ID; when Δd is greater than or equal to d m Continuously creating a track ID from the corresponding measured values, and comparing all measured values with the last measured value of each track ID in the newly received frame data until the same track ID is met, wherein d m =V m /f 0 ，d m Is a distance threshold, V m For the maximum speed limit of the current road section, f 0 Is the radar frame rate;
then, according to the number of the same track IDs obtained by accumulation, stable starting of the tracks is realized;
when at least 6 groups of tracks with the same track ID are included in the continuous 10-frame data, judging that the tracks are stable and start;
when the continuous 10-frame data comprise tracks with the same track ID of not more than 3 groups, judging that the tracks are false tracks and deleting the false tracks;
when more than 3 sets of tracks, but not more than 6 sets of identical track IDs are included in the continuous 10-frame data, the track is determined to be a temporary track by comparison with other measured values until the track is stably started.
In some embodiments, the step of configuring the track evaluation index for the track for which the track ID has been established at the track start stage includes:
obtaining the signal-to-noise ratio snr of N points contained in the track with built track ID 1 、snr 2 ……snr N ；
And weighting and averaging the signal to noise ratio to obtain a track evaluation index, wherein the track evaluation index comprises the following components:
In some embodiments, the step of associating newly received trace point data with the trace according to the trace evaluation index comprises:
sequencing the track evaluation indexes from high to low;
calculating the statistical distance between newly received point trace data and the track with the highest track evaluation index so as to calculate the point trace with the smallest statistical distance value;
comparing the newly received point track data with the last point track angle difference value of the last moment of the track in a threshold mode, defining the point track and the track meeting the threshold range as successfully associated, improving the current track evaluation index ranking of the track and deleting the newly received point track data;
and (3) sequentially repeating the calculation of the statistical distance and the threshold comparison of the tracks which do not meet the threshold range according to the sequence of the track evaluation index.
In some embodiments, the statistical distance calculation is formulated as:
in the method, in the process of the invention,
representing the statistical distance between the ith trace point data at the k moment and the flight path j;
representing the measurement residual error of the ith trace data and the trace j at the k moment, +.>
And the new covariance matrix of the track j at the moment k.
In some embodiments, the step of threshold comparing newly received trace point data to a last trace point angle difference value at a previous time on the trace includes:
the radial angle difference between newly received point trace data and the last point trace data at the previous moment of the track is calculated according to the following formula:
in the method, in the process of the invention,
is radial angle difference, & lt & gt>
The radial angle of the ith trace data at time k,
the radial angle of the last trace point data of the trace j at the time k-1 is set;
wherein when
Less than 10 °, indicating that the threshold range is met; when->
10 ° or more, indicating that the threshold range is not satisfied.
In some embodiments, the filtering process includes: filtering the trace point data by using an alpha-beta filter, wherein alpha is a filtering weight value, beta is a weight value of the trace point data obtained by the previous filtering, and
。
in some embodiments, the application further provides an electronic device, including a processor and a memory, where the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the steps of the radar signal processing method.
In some embodiments, the present application also provides a computer readable storage medium having stored therein at least one instruction or at least one program loaded and executed by a processor to implement the steps of the radar signal processing method.
The beneficial effects are that: compared with the prior art, the radar signal processing method provided by the application comprises the steps of acquiring frame data, preprocessing the frame data, and taking the trace points falling into the associated gate as target values; taking the target value as the first track point of the track, sequentially establishing a track ID, and comparing all measured values in the later frame of data with the measured values of the established track ID until the track is stably started; configuring a track evaluation index for the track of which the track ID is established in the track initial stage so that newly received point track data is associated with the track according to the track evaluation index; and filtering the trace point data successfully associated with the track to perform filtering estimation on the latest state of the track. The method of the application aims at the track configuration track evaluation index of the track ID established in the track initial stage, and adjusts the associated priority of the track according to the quantity of track associated to point track data, whether interruption exists or not and the like. When the new frame of track data is associated with the tracks, the tracks with higher track evaluation indexes are preferentially associated, the tracks with lower track evaluation indexes are considered as transient tracks, the association is considered later, and further observation is carried out according to the subsequent track data, so that the radar can track single and multiple targets with high precision, the distance limitation is avoided, the problem that the target data at a far position is not concentrated is solved, and the accuracy of the association of the target track at a far position and the tracks is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a radar signal processing method provided in an embodiment of the present application;
FIG. 2 is a block diagram of an electronic device according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of a radar signal processing procedure provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
In the description of the present application, it should be noted that the terms "first," "second," and the like are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
Referring to fig. 3, an echo signal received by a radar may detect a target through a signal processing system. The processing process mainly comprises target information confirmation, data association, tracking filtering and the like. The target tracking means that after the position and motion parameters (such as radial distance, radial speed, azimuth, pitch angle and the like) of the target are obtained, the target is subjected to data association with the existing track, the measurement points belonging to the existing track are confirmed to be used for updating the track filter parameters, and the data which are not associated are used for establishing a new track. Tracking state decisions are then made on the track, including detection, activation, and loss. And then predicting the position and the motion state of the track at the next moment, and forming a stable target track. And finally outputting the activated target track.
Referring to fig. 1, the present embodiment provides a radar signal processing method, including:
s101, acquiring frame data, preprocessing the frame data, and taking a point trace falling into an association gate as a target value;
s102, taking a target value as a first track point of a track, sequentially establishing a track ID, and comparing all measured values in the later frame of data with the measured values of the established track ID until the track is stably started;
s103, configuring a track evaluation index for the track of which the track ID is established in the track initial stage so that newly received point track data is associated with the track according to the track evaluation index;
s104, filtering processing is carried out on the track data successfully associated by the track so as to carry out filtering estimation on the latest state of the track.
In some embodiments, in S101, the preprocessing includes: detecting whether the data format of the frame header in the frame packet is complete or not, and filtering the data if the data format of the frame header is incomplete. If the data is complete, further judging whether the data falls into a detection range calibrated by the radar, and if the data does not fall into the detection range, filtering the data. Each frame of data detected by the radar comprises a preset frame header data format and target motion state information. The target state information includes distance, angle, speed, etc. The incomplete frame header indicates that the data transmission has errors, and the data error falling outside the radar detection range is larger, so that the data can be filtered out to reduce the subsequent calculation cost. From a large set of experimental data, it is shown that the higher the trace signal-to-noise ratio that falls within the correlation gate, the more likely it is to originate from the target. Assume that the signal to noise ratio of N traces falling into the associated gate is snr respectively 1 、snr 2 ……snr N The method comprises the steps of carrying out a first treatment on the surface of the And sorting the signal-to-noise ratio by a sorter, and selecting M points with the sorted signal-to-noise ratios from high to low as target values. Wherein, the value of M is referenced as follows:
M=(1-p)×N；
and P is calculated by considering the width of the center of mass of the point trace, if the number of the original point trace is N, p=N '/N, wherein N' is the number of the point trace outside the radar detection area. Therefore, the data volume can be adaptively adjusted according to the high-quality trace distribution of each detection frame, false targets caused by clutter and the like are eliminated, and the calculation cost is saved.
In some embodiments, in step S102, track IDs are sequentially established by using all track target values in the first frame data subjected to data preprocessing as the first track of the track. Assuming that the target is legal at a constant speed, the target can be considered asThe relative change in speed is small. In order to reduce the calculation cost, the radial distance difference between two adjacent frames is set as delta d, and the difference between all measured values in the data of the next frame and the measured value of the track ID established in the previous frame respectively meets delta d < d m If the track is the same track ID, the track is considered to be successfully associated with the track; wherein d m =V m /f 0 ，d m Is a distance threshold, V m For the maximum speed limit of the current road section, f 0 Is the radar frame rate.
If the new measurement value and all the previously established track IDs do not meet the threshold requirement, a track ID is newly established for the measurement value along the previously established track ID, and then all the measurement values in each newly received frame data are compared with the last measurement value of each track ID, and the comparison and judgment are carried out on the frame data by frame data according to the step until at least 6 groups of tracks with the same track ID are included in the continuous 10-frame data, the track is considered to be capable of stable starting. When the continuous 10 frames of data comprise tracks with no more than 3 groups of identical track IDs, the tracks can be considered as false tracks to be deleted directly; when more than 3 groups of tracks with the same track ID but not more than 6 groups of tracks are included in continuous 10 frames of data, the tracks can be regarded as temporary tracks, temporary reservation is realized, association judgment needs to be continued with the following tracks, and the observation processing of the temporary tracks can not be ended until a new stable track is formed.
It will be appreciated that after the track is initiated, the newly added measurement points need to be paired with and associated with the already initiated track, so as to maintain the track, and especially in an environment with more clutter and higher interference, multiple measurement values may be included in each frame of data, and among these measurement values, it cannot be directly determined which are the measurement values of the tracked target and which are false measurement values.
In some embodiments, in step S103, the track evaluation index is configured for the track for which the track ID has been established in the track start stage, and the association priority of the track is adjusted according to the number of track-to-point track data associated with the track and whether there is an interruption or not. When the new frame of track point data is associated with the tracks, the tracks with higher track evaluation indexes are preferentially associated, the tracks with lower track evaluation indexes are considered as transient tracks, the association is considered later, and further observation is carried out according to the subsequent track point data.
In the process of managing the tracks and performing data association, the tracks with the established track IDs are set to contain N points.
N point trace signal-to-noise ratios are respectively snr 1 、snr 2 ……snr N The corresponding weights are respectively:
And carrying out signal-to-noise ratio weighted average on all the points contained in the track to be used as an evaluation index of the track, determining the priority of track association according to the height of the track evaluation index, and preferentially associating the higher the evaluation index. Therefore, even if the number of the tracks is small, the signal to noise ratio of the tracks is high, the tracks can still be preferentially associated, so that the efficiency and the accuracy of track association can be improved. Then, carrying out multiple priority correlations according to the track evaluation index:
in the first correlation step, all the points in the new frame data are firstly calculated with the statistical distance with the track with the highest track evaluation index, the point with the smallest statistical distance value is calculated, and then whether the angle difference value between the point and the last point at the last moment of the track meets the threshold is considered. Specifically, the threshold is used to determine whether the angular difference is less than 10 °. If so, the track is considered to be successfully associated with the track, the current track evaluation index ranking of the track is improved, the newly received track data is deleted, and specifically, the associated track and the row and column where the track are located in a two-dimensional matrix formed by the frame data and the track can be deleted. If the angle difference threshold is not met, jumping to a track with a slightly lower track evaluation index, calculating the statistical distance between all the points and the track with the slightly lower track evaluation index, picking out the point data with the minimum distance, and judging the angle difference threshold.
In the first association, points which are not associated with the tracks are still in each frame of data after successful association, so that when the next association is performed, namely, in the residual matrix, points with the minimum statistical distance between the points and the tracks with the highest track evaluation index in the residual tracks are searched, meanwhile, the judgment is performed by using an angle difference wave gate, if the points are met, the current track evaluation index rank of the track is improved, the matrix row of the points and the tracks is deleted, otherwise, the track is skipped, and the next suboptimal track is subjected to association judgment.
In some embodiments, if there is only one trace within the associated wave gate, that trace is directly associated with the trace for which the trace ID has been established. If a plurality of tracks exist in the association gate, the statistical distance calculation is carried out on the newly received track data and the tracks with the built track IDs.
The formula of the statistical distance calculation is as follows:
in the method, in the process of the invention,
representing the statistical distance between the ith trace point data at the k moment and the flight path j;
representing the measurement residual error of the ith trace data and the trace j at the k moment, +.>
And the new covariance matrix of the track j at the moment k.
And then solving the radial angle difference between the new track and the last track data at the previous moment of the track, and carrying out constraint judgment on the radial angle difference according to the spherical wave gate, wherein the track meeting the threshold judgment condition is used as a candidate track of the track. On a traffic road, targets of two adjacent lanes are sometimes very near to each other, and due to limitation of resolution of the traffic radar, the traffic radar may misconsider multiple reflection points of the same target, so that the frequency spectrum of the echo signal is distributed in the adjacent resolution units, and the detected distance values are similarHowever, the angular resolution is higher, the angular parameter of the track data in the new frame will be significantly different from the angular value of the last track data in the previous frame, so the angular difference between the two tracks needs to be calculated
The traces within the angular constraint are considered candidate traces, taking into account the association.
The radial angle difference calculation formula is as follows:
in the method, in the process of the invention,
is radial angle difference, & lt & gt>
The radial angle of the ith trace data at time k,
the radial angle of the last trace point data of the trace j at the time k-1 is set;
wherein when
Less than 10 °, indicating that the threshold range is met; when->
10 ° or more, indicating that the threshold range is not satisfied.
It is noted that the calculation of the statistical distance between the track and the track can be converted into a two-dimensional allocation problem, the number i of the track data in each frame is a row, the number j of the track is a column, and a statistical distance matrix D is formed, which can be used for deleting the track data. The statistical distance matrix D is expressed as:
in some embodiments, in step S104, the latest state of the track is filter estimated using an adaptive alpha-beta filter for the successfully associated track. In this way, the radar can perform high-precision tracking processing of a single target and a plurality of targets. The alpha-beta filter wave is a simplified version of the kalman tracking filter. In the traditional Kalman filtering process, because one-step prediction of covariance calculation, innovation variance calculation and covariance updating are needed when the gain K (k+1) is calculated, the calculation amount is large, in order to effectively reduce the calculation amount, an alpha-beta filter for changing a gain matrix calculation method is provided, the gain is not related to the covariance any more, and the gain can be calculated offline in the filtering process.
The following assumptions are generally made: uniform motion and smooth observation of noise. Let the state vector be x= [ X, X ]'] T X and x' are the position and velocity vectors, respectively, then the target state equation is:
X k+1 =φX k +Gw k ；
wherein X is k+1 Represents the system state X of the alpha-beta filter at the k+1st moment k+1 Is a function of the estimated value of (2); state transition matrix
Input relation matrix->
The method comprises the steps of carrying out a first treatment on the surface of the Process noise w k Is zero as the mean value.
The observation equation is: z is Z k =HX k +v k ；
Wherein Z is k Representing the position observed quantity of the kth moment of the system; measurement matrix h= [ 10 ]]The method comprises the steps of carrying out a first treatment on the surface of the Measuring noise v k Is zero as the mean value.
The filter equation is:
X(k/k-1)=φX[(k-1)/(k+1)]；
X(k/k)= X(k/k-1)+K[Z k -HX(k/k-1)]；
K=[α，β/T] T k is the gain matrix.
Further, alpha is a filtering weight value, beta is a weight value of the trace point data obtained by the previous filtering, and
。
in some embodiments, in the next association, for all the remaining points and tracks, according to the previous steps, the selection of the point track with the smallest statistical distance is continued again, and the judgment is performed by using the angle difference wave gate. In the whole association process, according to different radial distances of target points, different angle difference value thresholds can be set so as to solve the problem that target data at a far position are not concentrated and improve the accuracy rate of association of the target points and tracks at a far position.
In some embodiments, an electronic device is provided that includes a processor and a memory having at least one instruction or at least one program stored therein, the at least one instruction or the at least one program loaded and executed by the processor to implement the steps of a radar signal processing method.
In some embodiments, referring to fig. 2, which is an internal block diagram of an electronic device provided in the present embodiment, the electronic device may be a server or a terminal, including a processor, a memory, and a communication interface connected to a system bus, where the processor is configured to provide control computing power of the computer device; the memory has stored thereon a computer program which, when executed by the processor, implements a method of traffic prediction. The memory includes a computer storage medium that is a non-volatile storage medium that stores an operating system and a computer program, and an internal memory that provides an environment for the operating system and the computer program to run. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be through WIFI, a mobile cellular network and the like.
In some embodiments, the structure shown in fig. 2 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device applied to the present application, and a specific electronic device may further include more or fewer components than those in fig. 2, or have different component arrangement connections, or some components combined, and so on.
In some embodiments, a computer readable storage medium having at least one instruction or at least one program stored therein is provided, the at least one instruction or the at least one program loaded and executed by a processor to implement the steps of a radar signal processing method.
In some embodiments, all or part of the above-mentioned radar signal processing method flow may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a non-volatile computer readable storage medium, and the computer program may include the flow of the above-mentioned embodiments of the method when executed. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic RandomAccess Memory, DRAM), and the like.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
The foregoing describes in detail a traffic early warning method and system provided by the embodiments of the present application, and applies specific examples to describe the principles and embodiments of the present application, where the descriptions of the foregoing embodiments are only used to help understand the technical solutions and core ideas of the present application; those of ordinary skill in the art will appreciate that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (8)
1. A method of radar signal processing, comprising:
acquiring frame data, preprocessing the frame data, and taking a point trace falling into an association gate as a target value;
taking the target value as the first track point of the track, sequentially establishing a track ID, and comparing all measured values in the later frame of data with the measured values of the established track ID until the track is stably started;
configuring a track evaluation index for a track of which the track ID is established in a track initial stage so that newly received point track data is associated with the track according to the track evaluation index;
filtering the trace point data successfully associated with the track to perform filtering estimation on the latest state of the track;
a step of configuring a track evaluation index for a track for which a track ID has been established at a track start stage, comprising:
obtaining the signal-to-noise ratio snr of N points contained in the track with built track ID 1 、snr 2 ……snr N ；
And weighting and averaging the signal to noise ratio to obtain a track evaluation index, wherein the track evaluation index comprises the following components:
the step of associating newly received trace point data with the track according to the track evaluation index comprises the following steps:
sequencing the track evaluation indexes from high to low;
calculating the statistical distance between newly received point trace data and the track with the highest track evaluation index so as to calculate the point trace with the smallest statistical distance value;
comparing the newly received point track data with the last point track angle difference value of the last moment of the track in a threshold mode, defining the point track and the track meeting the threshold range as successfully associated, improving the current track evaluation index ranking of the track and deleting the newly received point track data;
and (3) sequentially repeating the calculation of the statistical distance and the threshold comparison of the tracks which do not meet the threshold range according to the sequence of the track evaluation index.
2. The radar signal processing method according to claim 1, wherein the step of preprocessing the frame data includes:
detecting the integrity degree of the data format of the frame header in the frame data, and filtering out the frame data with incomplete data format; and/or the number of the groups of groups,
judging the position relation between the frame data and the association gate, and filtering the frame data which does not fall into the association gate.
3. A radar signal processing method according to claim 1, wherein the step of comparing all measured values in the subsequent frame of data with measured values for which track ID has been established until the start of track stabilization comprises:
firstly, acquiring a radial distance difference delta d between a measured value in the data of the next frame and a measured value of the established track ID; when Δd < d m When the two measured values belong to the same track ID, judging that the two measured values belong to the same track ID; when Δd is greater than or equal to d m Continuously creating a track ID from the corresponding measured values, and comparing all measured values with the last measured value of each track ID in the newly received frame data until the same track ID is met, wherein d m =V m /f 0 ，d m Is a distance threshold, V m For the maximum speed limit of the current road section, f 0 Is the radar frame rate;
then, according to the number of the same track IDs obtained by accumulation, stable starting of the tracks is realized;
when at least 6 groups of tracks with the same track ID are included in the continuous 10-frame data, judging that the tracks are stable and start;
when the continuous 10-frame data comprise tracks with the same track ID of not more than 3 groups, judging that the tracks are false tracks and deleting the false tracks;
when more than 3 sets of tracks, but not more than 6 sets of identical track IDs are included in the continuous 10-frame data, the track is determined to be a temporary track by comparison with other measured values until the track is stably started.
4. The method of claim 1, wherein the formula for calculating the statistical distance is:
in the method, in the process of the invention,
representing the statistical distance between the ith trace point data at the k moment and the flight path j; />
Representing the measurement residual error of the ith trace data and the trace j at the k moment, +.>
And the new covariance matrix of the track j at the moment k.
5. The method of claim 4, wherein the step of threshold comparing newly received trace data with a trace angle difference last at a previous time on the trace comprises:
the radial angle difference between newly received point trace data and the last point trace data at the previous moment of the track is calculated according to the following formula:
in the method, in the process of the invention,
is radial angle difference, & lt & gt>
The radial angle of the ith trace data at time k,
the radial angle of the last trace point data of the trace j at the time k-1 is set;
wherein when
Less than 10 °, indicating that the threshold range is met; when->
10 ° or more, indicating that the threshold range is not satisfied.
6. A radar signal processing method according to claim 1, wherein the filtering process comprises: filtering the trace point data by using an alpha-beta filter, wherein alpha is a filtering weight value, beta is a weight value of the trace point data obtained by the previous filtering, and
。
7. an electronic device comprising a processor and a memory, wherein at least one instruction or at least one program is stored in the memory, the at least one instruction or the at least one program being loaded and executed by the processor to implement the steps of the radar signal processing method according to any one of claims 1 to 6.
8. A computer readable storage medium having stored therein at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by a processor to implement the steps of the radar signal processing method according to any one of claims 1 to 6.
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