Radar target track confidence coefficient determination method, electronic equipment and storage medium

Abstract

The invention relates to the technical field of radars, and discloses a method for determining the track confidence of a radar target, electronic equipment and a storage medium, and the method comprises the steps: obtaining a current detection point, a track estimation value and a track prediction value obtained when a radar detects the radar target at the current moment; a first square value is determined, and the first square value is the square value of the mahalanobis distance between the track estimation value and the track prediction value; according to the number of the current detection points and the first square value, determining a first confidence coefficient of a track of the radar target at the current moment formed by the current detection points from a preset data table, the data table storing a corresponding relationship between the number of the detection points and the square value of the mahalanobis distance, the squared value of the mahalanobis distance and the first confidence coefficient are obtained; and determining the track confidence of the radar target according to the first confidence. According to the invention, the track confidence of the radar target can be rapidly and accurately determined.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of radar technology, and specifically to a method for determining track confidence of a radar target, an electronic device, and a storage medium. Background Art

[0002] As radar is increasingly used in military equipment, civilian and other fields, the market has put forward more stringent requirements on the overall performance and reliability of radar. Radar is not only required to detect targets within the field of view, but also to be able to reshape, track and predict the motion trajectory information of the detected targets, that is, the radar is required to process radar data sets, which is usually called radar information processing, also known as radar target tracking.

[0003] By tracking the radar target, the track of the radar target can be obtained, so the result of radar target tracking is called radar target track information. Based on the confidence of the radar target track, the danger level and threat level of the radar target can be evaluated, so as to provide early warning and defense for the radar target. At present, there is a lack of a method that can quickly and accurately determine the confidence of the radar target track. Summary of the invention

[0004] In view of the above problems, an embodiment of the present application provides a method for determining the track confidence of a radar target, an electronic device and a storage medium, which are used to solve the problem in the prior art that the confidence of the track of a radar target cannot be determined quickly and accurately.

[0005] According to one aspect of an embodiment of the present application, a method for determining track confidence of a radar target is provided, the method comprising: obtaining a current detection point, a track estimation value and a track prediction value obtained by detecting a radar target by a radar at a current moment, wherein the track estimation value is position information of the radar target at the current moment estimated from information of the current detection point, and the track prediction value is position information of the radar target at the current moment obtained by predicting the track of the radar target at a historical moment; determining a first square value, wherein the first square value is the square value of the Mahalanobis distance between the track estimation value and the track prediction value; determining a first confidence of the track of the radar target at the current moment formed by the current detection point from a preset data table according to the number of the current detection points and the first square value, wherein the data table stores a correspondence between the number of detection points and the square value of the Mahalanobis distance, and a correspondence between the square value of the Mahalanobis distance and the first confidence; determining the track confidence of the radar target according to the first confidence.

[0006] In an optional manner, the first square value is S q, the first confidence level of the track of the radar target at the current moment formed by the current detection point is determined from a preset data table according to the number of the current detection points and the first square value, including: determining the square values ​​of all Mahalanobis distances corresponding to the number of the current detection points in the data table; determining a second square value S from the square values ​​of all Mahalanobis distances q ', where the S q and the S q The relationship between ′ satisfies S q >S q ′ and S q ≤S q ″,S q ′ and S q ″ is the two adjacent square values ​​of all the square values ​​of the Mahalanobis distances sorted from small to large; the second square value S in the data table is q The confidence level corresponding to ′ is determined as the first confidence level.

[0007] In an optional manner, before determining the track confidence of the radar target according to the first confidence, the method further includes: judging whether the number of the current detection points is greater than or equal to a preset threshold, wherein the preset threshold is related to the distance between the radar target and the radar at the current moment and the volume of the radar target; if the number of the current detection points is greater than or equal to the preset threshold, determining a first value as a second confidence of the track of the radar target at the current moment formed by the current detection points; if the number of the current detection points is less than the preset threshold, determining a second value according to the number of the current detection points and the preset threshold, and determining the second value as the second confidence of the track of the radar target at the current moment formed by the current detection points, wherein the second value is less than the first value; determining the track confidence of the radar target according to the first confidence includes: determining the track confidence according to the first confidence and the second confidence.

[0008] In an optional manner, before determining the track confidence based on the first confidence and the second confidence, the method also includes: obtaining a current update status value corresponding to the current moment, and n historical update status values ​​corresponding to n historical moments, wherein the update status value corresponding to a certain moment is used to characterize the degree of matching between the track prediction value and the track estimation value corresponding to the moment, and n is a positive integer; determining a third confidence based on the current update status value and the n historical update status values; determining the track confidence based on the first confidence and the second confidence includes: determining the track confidence based on the first confidence, the second confidence and the third confidence.

[0009] In an optional manner, determining the third confidence level based on the current update status value and n historical update status values ​​includes: respectively obtaining the weights corresponding to the current moment and each of the historical moments; determining the third confidence level based on the weights corresponding to the current moment and each of the historical moments and the update status value.

[0010] In an optional manner, the n historical moments are the n historical moments closest to the current moment, the weights corresponding to the current moment are greater than or equal to the weights corresponding to the n historical moments, and W i ≥W j , where W i and W j are the weights corresponding to the i-th historical moment and the j-th historical moment in the n historical moments, respectively, and the i-th historical moment is later than the j-th historical moment, i and j are both positive integers, i≤n, j≤n; determining the third confidence level according to the weights corresponding to the current moment and each of the historical moments and the update state value, including: determining the third confidence level according to the formula Determine the third confidence level p3, where s l and pr l They are respectively the updated state value and the weight corresponding to the current moment and the lth moment among the n historical moments.

[0011] In an optional manner, determining the track confidence based on the first confidence, the second confidence and the third confidence includes: obtaining the first weight, the second weight and the third weight corresponding to the first confidence, the second confidence and the third confidence respectively, wherein the sum of the first weight, the second weight and the third weight is 1; determining the track confidence based on the first confidence, the second confidence, the third confidence, the first weight, the second weight and the third weight.

[0012] In an optional manner, the track confidence is determined based on the first confidence, the second confidence, the third confidence, the first weight, the second weight and the third weight, including: respectively determining a first product of the first confidence and the first weight, a second product of the second confidence and the second weight, and a third product of the third confidence and the third weight; determining the sum of the first product, the second product and the third product; judging whether the sum is less than or equal to a preset value; if the sum is less than or equal to the preset value, determining the track confidence based on the sum; if the sum is greater than the preset value, determining the preset value as the track confidence.

[0013] According to another aspect of an embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the above-mentioned method for determining track confidence of a radar target.

[0014] According to another aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for determining the track confidence of the radar target described above is implemented.

[0015] In the embodiment of the present application, by calculating the square value of the Mahalanobis distance between the track estimate and the track prediction value, and looking up the table according to the preset data table and the square value, the first confidence level can be quickly determined, and the confidence level of the track of the radar target at the current moment formed by the current detection point can be quickly determined according to the first confidence level, thereby improving the efficiency of determining the confidence level of the track. Since the embodiment of the present application is determined based on the Mahalanobis distance between the track estimate and the track prediction value, and different Mahalanobis distances can reflect the statistical characteristics of the track estimate and the degree of closeness to the track itself, and the square value of the Mahalanobis distance obeys the chi-square distribution, the accuracy of the determined first confidence level is improved.

[0016] The above description is only an overview of the technical solution of the embodiment of the present application. In order to more clearly understand the technical means of the embodiment of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present application. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0018] Figure 1 A schematic diagram of a flow chart of a method for determining track confidence of a radar target provided in an embodiment of the present application is shown;

[0019] Figure 2 A schematic diagram of a flow chart of a method for determining track confidence of a radar target provided in another embodiment of the present application is shown;

[0020] Figure 3 A schematic diagram of a flow chart of a method for determining track confidence of a radar target provided in yet another embodiment of the present application is shown;

[0021] Figure 4 The embodiment of the present application provides Figure 3 A schematic flow chart of sub-steps of step 310;

[0022] Figure 5 A schematic diagram of the structure of a device for determining track confidence of a radar target provided in an embodiment of the present application is shown;

[0023] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0024] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0025] The detection points obtained by multiple detection of radar targets by radar are processed by point trace processing, radar target filtering, radar target association, etc., to obtain the motion trajectory information of the radar target, that is, the track of the radar target. The track confidence of the radar target refers to the probability that the track of the radar target formed by the detection points obtained by detecting the radar target by the radar actually exists, that is, the probability that the track formed by the detection points belongs to the track of the radar target. Since the detection points obtained by the radar for detecting the radar target may belong to false targets, where the false targets refer to radar targets that are not tracked by the radar, such as interference objects near the radar target, if the confidence of the track formed by the detection points is not evaluated, and the track formed by the detection points is directly assumed to be the track of the radar target, the track of the false target may be mistakenly regarded as the track of the radar target, and then a large error will be generated in the subsequent evaluation of the danger level and threat level of the radar target. In general, determining the confidence of the track formed by the detection points is crucial to radar target tracking. The higher the confidence of the track formed by the detection points, the greater the probability that the track formed by the detection points belongs to the track of the radar target rather than the track of the false target.

[0026] When evaluating the track confidence, an evaluation index system is established according to the position information of the radar target, and the evaluation index is calculated using a recursive calculation method. Then, the weighted coefficient of the evaluation index is determined according to the hierarchical analysis method, and finally, the quality of the radar target track is comprehensively evaluated using the weighted summation method. Evaluating the confidence of the radar target track is a key technology in radar target tracking processing. Existing radar target track confidence evaluation methods include measurement / track association methods such as nearest neighbor, probabilistic data association, joint probabilistic data association, and multi-hypothesis tracking, as well as track association methods based on statistical methods or fuzzy mathematics. However, these methods have many prerequisites for use, and there are many related quantities involved when using these methods, which leads to certain complexity and computational complexity in evaluating the track confidence of radar targets using these methods.

[0027] Based on the above considerations, in order to quickly and accurately determine the track confidence of a radar target, the present application proposes a method for determining the track confidence of a radar target. At the current moment, the radar detects the radar target to obtain a detection point. According to the detection point, the track estimation value of the radar target can be estimated. According to the track prediction of the radar target at the historical moment, the track prediction value of the radar target at the current moment is obtained. The square value of the Mahalanobis distance between the track estimation value and the track prediction value is calculated, and then the corresponding probability between the Mahalanobis distance and the chi-square test threshold is used to determine the track confidence of the radar target.

[0028] Figure 1 A flow chart of a method for determining track confidence of a radar target provided in an embodiment of the present application is shown, and the method is executed by an electronic device (e.g., a radar), and the electronic device may be an electronic device including one or more processors, and the processor may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement an embodiment of the present invention, which is not limited here. The one or more processors included in the electronic device may be processors of the same type, such as one or more CPUs; or may be processors of different types, such as one or more CPUs and one or more ASICs, which is not limited here.

[0029] like Figure 1 As shown, the method comprises the following steps:

[0030] Step 110: Obtain the current detection point, track estimation value and track prediction value obtained by the radar detecting the radar target at the current moment, wherein the track estimation value is the position information of the radar target at the current moment estimated from the information of the current detection point, and the track prediction value is the position information of the radar target at the current moment obtained by predicting the track of the radar target at historical moments.

[0031] Among them, the radar target in the embodiment of the present application refers to a moving target detected by the radar, such as a moving pedestrian, vehicle or drone. The radar sends a detection signal to the radar target and receives the signal reflected by the radar target, and then analyzes the signal reflected by the radar target to determine the position, moving speed and other information of the radar target to achieve the detection of the radar target. Since the radar target has a certain shape and volume, after the radar sends a detection signal to the radar target, the signal will be reflected at one or more points of the radar target, so that the signal reflected by one or more points belonging to the radar target will be obtained, that is, one or more detection points obtained by the radar detecting the radar target. Usually the detection point includes attribute information of the radar target, such as the position information corresponding to the detection point, the distance information between the radar and the radar, the speed information, etc.

[0032] Since the radar target in the embodiment of the present application is a moving target, the information of the detection point obtained by the radar detecting the radar target at different times is not exactly the same, for example, the position information corresponding to the detection point obtained by detecting the radar target at different times is different. In the embodiment of the present application, the detection point obtained by the radar detecting the radar target at the current moment is the current detection point. It should be noted that in the present application, the current moment refers to the same moment.

[0033] It is understandable that the track of a radar target within a certain period of time is composed of the position information of the radar target at multiple different times within the period of time. In the embodiment of the present application, the track estimation value specifically refers to the position information of the radar target at the current moment estimated by the information of the current detection point. As described above, since the detection point includes the position information corresponding to the point, the position information of the radar target at the current moment can be estimated by the position information of the current detection point, thereby obtaining the track estimation value. For example, the position corresponding to a certain detection point is directly estimated as the position of the radar target at the current moment.

[0034] The track prediction value specifically refers to the position information of the radar target at the current moment obtained by predicting the track of the radar target at the historical moment. Since the radar target is a moving target, by continuously detecting the radar target, the detection points of the radar target at multiple moments are obtained, and the position information and speed information of the radar target at multiple moments are obtained. Then, the position of the radar target at the current moment can be predicted based on the position information and speed information of the radar target at multiple moments in history, thereby obtaining the track prediction value.

[0035] Step 120: Determine a first square value, wherein the first square value is the square value of the Mahalanobis distance between the track estimation value and the track prediction value.

[0036] In this step, the Mahalanobis distance between the track estimate and the track prediction is first calculated, and then the square value of the Mahalanobis distance is calculated. The final square value is the first square value. Determine the square of the Mahalanobis distance between the track estimate and the track prediction Among them, the new information is Z(k+1) is the estimated value of the track, is the track prediction value, the measurement equation is Z(k+1)=H(k+1)X(k+1)+W(k+1), where H(k+1) is the measurement matrix, X(k+1) is the state vector, and W(k+1) is a zero-mean, white Gaussian measurement noise sequence with covariance R(k+1). The innovation covariance is S(k+1)=H(k+1)P(k+1|k)H′(k+1)+R(k+1), and P(k+1|k) is the one-step prediction of the covariance.

[0037] Step 130: According to the number of current detection points and the first square value, determine the first confidence of the track of the radar target at the current moment formed by the current detection points from a preset data table, wherein the data table stores the correspondence between the number of detection points and the square value of the Mahalanobis distance, and the correspondence between the square value of the Mahalanobis distance and the first confidence.

[0038] Among them, the data table is set based on the chi-square distribution table. In this step, the first square value corresponding to the number of current detection points can be determined from the data table first, and then the confidence corresponding to the first square value can be determined from the data table. The confidence is the first confidence. The stability of the track of the radar target can be represented by the Mahalanobis distance between the track estimation value and the track prediction value, that is, different Mahalanobis distances can reflect the degree of closeness between the statistical characteristics of the track estimation value and the track of the radar target itself. Since the square value of the Mahalanobis distance obeys the chi-square distribution, the degree of closeness can be described by the probability corresponding to the Mahalanobis distance and the chi-square test threshold. When the number of current detection points is the same, if the square value of the Mahalanobis distance is smaller, it means that the track of the radar target at the current moment estimated according to the current detection point is closer to the track of the radar target at the current moment predicted according to the track of the radar target at the historical moment, that is, it means that the confidence of the track of the radar target formed according to the current detection point is higher.

[0039] Step 140: Determine the track confidence of the radar target according to the first confidence.

[0040] Among them, in the embodiment of the present application, the first confidence level can be directly determined as the track confidence level of the radar target.

[0041] In the embodiment of the present application, by calculating the square value of the Mahalanobis distance between the track estimate and the track prediction value, and looking up the table according to the preset data table and the square value, the first confidence level can be quickly determined, and the confidence level of the track of the radar target at the current moment formed by the current detection point can be quickly determined according to the first confidence level, thereby improving the efficiency of determining the confidence level of the track. Since the embodiment of the present application is determined based on the Mahalanobis distance between the track estimate and the track prediction value, and different Mahalanobis distances can reflect the statistical characteristics of the track estimate and the degree of closeness to the track itself, and the square value of the Mahalanobis distance obeys the chi-square distribution, the accuracy of the determined first confidence level is improved.

[0042] In order to further improve the accuracy of determining the first confidence level from the data table, in the embodiment of the present application, step 130 includes the following steps a01 to a03.

[0043] Step a01: Determine the square values ​​of all Mahalanobis distances corresponding to the number of current detection points in the data table.

[0044] Among them, Table 1 is a data table provided in an embodiment of the present application, and the data table is set based on the chi-square distribution table. As shown in Table 1, the data table stores the square values ​​of the Mahalanobis distances corresponding to the number of detection points of 1 to 30, and the first confidence corresponding to the square values ​​of different Mahalanobis distances. Taking the number of detection points as 7 as an example, the corresponding square values ​​of all Mahalanobis distances are 0.989, 1.239, 1.69, 2.167, 2.833, 12.017, 14.067, 16.013, 18.475 and 20.278.

[0045] Table 1:

[0046]

[0047] For the convenience of description, the first square value is defined as S q .

[0048] Step a02: Determine the second square value S from the square values ​​of all Mahalanobis distances q ′, where S q and S q The relationship between ′ satisfies S q >S q ′ and S q ≤S q ″,S q ′ and S q ″ is the two adjacent square values ​​of all Mahalanobis distances sorted from small to large.

[0049] Among them, taking the number of detection points as 7 as an example, if the first square value S q is 1.5, then the second square value S q ′ is 1.239, S q ″ is 1.69.

[0050] Step a03: The second square value S in the data table q The confidence level corresponding to ′ is determined as the first confidence level.

[0051] Among them, the number of detection points is 7, the first square value S q Taking 1.5 as an example, the first confidence level is the first confidence level 0.99 corresponding to the square value of the Mahalanobis distance of 1.239 in Table 1.

[0052] In the embodiment of the present application, the second square value S is determined from the square values ​​of all Mahalanobis distances. q ′, and the second square value S q ′ is determined as the first confidence level. q and S q The relationship between ′ satisfies S q >S q′ and S q ≤S q ”, thereby avoiding the situation where the determined first confidence is too large, and also improving the accuracy of the determined first confidence.

[0053] Figure 2 FIG. 2 is a flow chart of a method for determining the track confidence of a radar target provided by another embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0054] Step 201: Obtain the current detection point, track estimation value and track prediction value obtained by the radar detecting the radar target at the current moment, wherein the track estimation value is the position information of the radar target at the current moment estimated from the information of the current detection point, and the track prediction value is the position information of the radar target at the current moment obtained by predicting the track of the radar target at the historical moment.

[0055] Step 202: Determine a first square value, wherein the first square value is the square value of the Mahalanobis distance between the track estimation value and the track prediction value.

[0056] Step 203: According to the number of current detection points and the first square value, determine the first confidence of the track of the radar target at the current moment formed by the current detection points from a preset data table, wherein the data table stores the correspondence between the number of detection points and the square value of the Mahalanobis distance, and the correspondence between the square value of the Mahalanobis distance and the first confidence.

[0057] Among them, steps 201 to 203 are the same as steps 110 to 130, so the principles and implementation methods of steps 201 to 203 can refer to steps 110 to 130, and will not be repeated here.

[0058] Step 204: Determine whether the number of current detection points is greater than or equal to a preset threshold, wherein the preset threshold is related to the distance between the radar target and the radar at the current moment and the volume of the radar target. If yes, go to step 205; if not, go to step 206.

[0059] Among them, after the radar transmits a signal to the radar target, it can receive the signal reflected back from the point on the surface of the radar target, that is, the detection point is obtained. Therefore, it can be understood that, when the distance between the radar and the radar target is the same, if the volume of the radar target is larger, the number of detection points obtained after the radar transmits the same signal to the radar target is more. When the volume of the radar target is the same, if the distance between the radar and the radar target is smaller, the number of detection points obtained after the radar transmits the same signal to the radar target is more. In the embodiment of the present application, by setting a preset threshold, it is possible to determine whether the current detection point obtained in step 201 belongs to the point of the radar target according to the size relationship between the number of current detection points and the preset threshold. The preset threshold can be set according to the volume of the radar target and the distance between the radar target and the radar, which is not limited here. Specifically, the corresponding relationship between the volume of the radar target and the preset threshold, as well as the corresponding relationship between the distance between the radar target and the radar and the preset threshold can be pre-stored, and after determining all the preset thresholds corresponding to the volume of the radar target from the corresponding relationship between the volume of the radar target and the preset threshold, the preset threshold corresponding to the distance between the radar target and the radar at the current moment is determined from all the preset thresholds.

[0060] Step 205: Determine the first value as the second confidence level of the track of the radar target formed by the current detection point at the current moment.

[0061] The first value can be set as needed, such as 0.9 or 1. In the embodiment of the present application, if the number of current detection points is greater than or equal to the preset threshold, it means that the current detection point belongs to the radar target. Therefore, preferably, the first value is 1, that is, the probability that the track formed by the current detection point belongs to the track of the radar target is 1.

[0062] Step 206: Determine a second value according to the number of current detection points and a preset threshold, wherein the second value is less than the first value. The second value can be determined as needed. If the number of current detection points is less than the preset threshold, it means that the current detection point does not necessarily belong to the radar target. Therefore, the second value can be determined according to the number of detection points and the preset threshold.

[0063] In the embodiment of the present application, preferably, step 206 includes: determining a ratio of the number of current detection points to a preset threshold, and determining the ratio as a second value, wherein the larger the ratio, the greater the probability that the current detection point belongs to a radar target.

[0064] In some embodiments, the second value can also be determined by other means. For example, if the difference between the current number of detection points and the preset threshold is small, it means that the probability that the current detection point belongs to the radar target is large, so the second value is determined to be 1; if the difference between the current number of detection points and the preset threshold is large, it means that the probability that the current detection point belongs to the radar target is small, so the second value is determined to be 0.2 or 0.3.

[0065] Step 207: Determine the second value as the second confidence level of the track of the radar target formed by the current detection point at the current moment.

[0066] Step 208: Determine the track confidence level according to the first confidence level and the second confidence level.

[0067] Among them, in the embodiment of the present application, after determining the first weight corresponding to the first confidence and the second weight corresponding to the second confidence, the first product of the first confidence and the first weight, and the second product of the second confidence and the second weight are determined, and the sum of the first product and the second product is determined as the track confidence of the radar target at the current moment formed by the current detection point. The first weight and the second weight can be set as needed, without limitation here, for example, the first weight and the second weight are both 0.5, or the first weight is 0.6, and the second weight is 0.4. In some embodiments, the lower confidence of the first confidence and the second confidence can also be determined as the track confidence, or the higher confidence of the first confidence and the second confidence can be determined as the track confidence.

[0068] It is understandable that there may be errors when the radar detects the radar target, that is, there may be a situation where the detection point obtained does not belong to the radar target. The probability of reliability of the track clustering of the radar target can be expressed as the ratio of the number of detection points that are close to the attributes of the radar target (the location information, motion characteristics, etc. of the radar target) and can be matched with the cluster at the current moment to the preset detection point number threshold (i.e., the preset threshold). In the embodiment of the present application, preferably, by determining the second confidence of the track of the radar target at the current moment formed by the current detection point according to the number of current detection points and the preset threshold, the larger the ratio of the number of current detection points to the preset threshold, the greater the probability that the current detection point belongs to the radar target, that is, the second confidence of the track of the radar target at the current moment formed by the current detection point is higher. Since the preset threshold is related to the distance between the radar target and the radar at the current moment and the volume of the radar target, the accuracy of the second confidence determined by the embodiment of the present application in the above manner is higher.

[0069] Since the first confidence level and the second confidence level belong to the confidence levels of the track of the radar target at the current moment formed by the current detection point determined from two different dimensions, in the embodiment of the present application, the confidence level of the track of the radar target at the current moment formed by the current detection point is ultimately determined by the first confidence level and the second confidence level, which further improves the accuracy of the ultimately determined track confidence level compared to the method of directly determining the track confidence level from a single dimension.

[0070] It is worth noting that in the embodiment of the present application, the execution order of step 202 and step 204 can be determined as needed. For example, steps 202 to 203 can be executed first, and then steps 204 to 207; steps 204 to 207 can be executed first, and then steps 202 to 203; steps 202 to 203 and steps 204 to 207 can also be executed at the same time.

[0071] Figure 3 FIG. 2 is a flow chart of a method for determining the track confidence of a radar target provided by another embodiment of the present application. Figure 3 As shown, the method comprises the following steps:

[0072] Step 301: Obtain the current detection point, track estimation value and track prediction value obtained by the radar detecting the radar target at the current moment, wherein the track estimation value is the position information of the radar target at the current moment estimated from the information of the current detection point, and the track prediction value is the position information of the radar target at the current moment obtained by predicting the track of the radar target at historical moments.

[0073] Step 302: Determine a first square value, where the first square value is the square value of the Mahalanobis distance between the track estimation value and the track prediction value.

[0074] Step 303: According to the number of current detection points and the first square value, determine the first confidence of the track of the radar target at the current moment formed by the current detection points from a preset data table, wherein the data table stores the correspondence between the number of detection points and the square value of the Mahalanobis distance, and the correspondence between the square value of the Mahalanobis distance and the first confidence.

[0075] Step 304: Determine whether the number of current detection points is greater than or equal to a preset threshold, wherein the preset threshold is related to the distance between the radar target and the radar at the current moment and the volume of the radar target. If yes, go to step 305; if not, go to step 306.

[0076] Step 305: Determine the first value as the second confidence level of the track of the radar target formed by the current detection point at the current moment.

[0077] Step 306: Determine a second value according to the number of current detection points and a preset threshold, wherein the second value is smaller than the first value.

[0078] Step 307: Determine the second value as the second confidence level of the track of the radar target formed by the current detection point at the current moment.

[0079] Among them, steps 301 to 307 are the same as steps 201 to 207, so the principles and implementation methods of steps 301 to 307 can refer to steps 201 to 207, and will not be repeated here.

[0080] Step 308: Obtain the current update status value corresponding to the current moment and n historical update status values ​​corresponding to n historical moments, wherein the update status value corresponding to a certain moment is used to characterize the matching degree between the track prediction value and the track estimation value corresponding to the moment, and n is a positive integer.

[0081] Among them, n historical moments refer to n historical moments earlier than the current moment. n can be set as needed, for example, n is 2, 3 or 5, etc. In the embodiment of the present application, preferably, the n historical moments are the n historical moments closest to the current moment. Among them, the update status value obtained in this step is the status value output by other modules. For the update status value at a certain moment, it represents the state of the detection information update of whether the track of the radar target at that moment is detected, and the update status value can be determined according to the track prediction value and track estimation value corresponding to the moment. Specifically, the matching degree of the track prediction value and the track estimation value corresponding to the moment can be calculated first, and the update status value corresponding to the moment is determined according to the matching degree. For example, if the matching degree corresponding to the moment is greater than the matching degree threshold, the update status value corresponding to the moment is determined to be 1, and if the matching degree corresponding to the moment is less than or equal to the matching degree threshold, the update status value corresponding to the moment is determined to be 0. It can be understood that for the matching degree corresponding to a certain moment, the absolute difference between the track prediction value and the track estimation value corresponding to the moment can be calculated, and the absolute difference can be determined as the matching degree. For example, the matching degree corresponding to the moment is (1-|xy|), where x and y are the track prediction value and the track estimation value, respectively; the relative difference corresponding to the moment can also be calculated, and the relative difference can be determined as the matching degree. For example, the matching degree corresponding to the moment is (1-|(xy) / max(x, y)|). The matching degree threshold can be set as needed and is not limited here.

[0082] Step 309: Determine a third confidence level according to the current update status value and n historical update status values.

[0083] In the embodiment of the present application, preferably, step 309 includes: obtaining the weights corresponding to the current moment and each historical moment respectively, and determining the third confidence level according to the weights corresponding to the current moment and each historical moment respectively and the update state value. The weights corresponding to the current moment and each historical moment respectively are preset, and the specific weights can be set as needed.

[0084] In the embodiment of the present application, preferably, according to the formula Determine the third confidence level p3, where s l and pr l They are the updated state values ​​and weights corresponding to the current moment and the nth moment in the n historical moments.

[0085] In some embodiments, the current update status value and the largest update status value among the n historical update status values ​​can be used as the third confidence level, the smallest update status value can be used as the third confidence level, or the average value of the current update status value and the n historical update status values ​​can be used as the third confidence level.

[0086] Step 310: Determine the track confidence according to the first confidence, the second confidence and the third confidence.

[0087] Among them, in an embodiment of the present application, preferably, the first weight, second weight and third weight corresponding to the first confidence, the second confidence and the third confidence are obtained respectively, and the track confidence is determined according to the first confidence, the second confidence, the third confidence, the first weight, the second weight and the third weight, wherein the sum of the first weight, the second weight and the third weight is 1.

[0088] The stability probability of the radar target's track in the time domain can be described as the state of the detection point information associated with each moment at the current moment and n historical moments. Whether the radar target exists in the time domain and the degree of stability of its existence are expressed by probability, which is the stability probability of the radar target's track in the time domain.

[0089] Therefore, in an embodiment of the present application, by analyzing the updated state values ​​corresponding to multiple historical moments and the current moment, the stability probability of the radar target's track in the time domain is determined, that is, the third confidence level of the radar target's track at the current moment formed by the current detection point is determined from the time domain dimension. If the third confidence level is high, it means that the radar target's track at multiple historical moments and the current moment is stably present in the time domain.

[0090] Since the first confidence level, the second confidence level, and the third confidence level belong to the confidence levels of the track of the radar target at the current moment formed by the current detection point determined from three different dimensions, in the embodiment of the present application, the confidence level of the track of the radar target at the current moment formed by the current detection point is ultimately determined by the first confidence level, the second confidence level, and the third confidence level. Compared with the method of directly determining the track confidence level from a single dimension, the accuracy of the ultimately determined track confidence level is further improved.

[0091] It is worth noting that in the embodiment of the present application, the execution order of step 302, step 304 and step 308 can be determined as needed. For example, steps 302 to 303 can be executed first, then steps 304 to 307, and then steps 308 to 309; steps 302 to 303 can be executed first, then steps 308 to 309, and then steps 304 to 307; steps 302 to 303, steps 304 to 307 and steps 308 to 309 can also be executed simultaneously. The execution order of steps 302, step 304 and step 308 is not listed one by one here.

[0092] In some embodiments, the n historical moments are the n historical moments closest to the current moment, and are calculated by the formula When determining the third confidence level p3, the weight corresponding to the current moment is greater than or equal to the weight corresponding to each of the n historical moments, and W i ≥W j , where W i and W j are the weights corresponding to the ith historical moment and the jth historical moment in n historical moments, respectively, and the ith historical moment is later than the jth historical moment, i and j are both positive integers, i≤n, j≤n. The sum of the weights corresponding to all moments is 1.

[0093] In the embodiment of the present application, since it is necessary to determine the stability of the track of the radar target in the time domain, the track of the radar target formed by the historical detection points corresponding to the historical moments closer to the current moment has a greater influence on determining the third confidence level. Therefore, in the embodiment of the present application, the weight corresponding to the current moment is set to be greater than or equal to the weight corresponding to each of the n historical moments, and W i ≥W j , thereby improving the accuracy of the determined third confidence level, and thus improving the accuracy of the ultimately determined track confidence level.

[0094] Figure 4 The embodiment of the present application provides Figure 3 Schematic diagram of the sub-step flow chart of step 310.

[0095] like Figure 4As shown, step 310 includes:

[0096] Step 3101: Obtain the first weight, the second weight and the third weight corresponding to the first confidence, the second confidence and the third confidence respectively, wherein the sum of the first weight, the second weight and the third weight is 1.

[0097] The first weight, the second weight and the third weight are all preset. The first weight, the second weight and the third weight can be set as needed, for example, the first weight is set to 0.4, the second weight is set to 0.4, and the third weight is set to 0.2.

[0098] Step 3102: Determine respectively a first product of a first confidence and a first weight, a second product of a second confidence and a second weight, and a third product of a third confidence and a third weight.

[0099] Step 3103: Determine the sum of the first product, the second product and the third product.

[0100] Step 3104: Determine whether the sum is less than or equal to a preset value. If yes, go to step 3105; if no, go to step 3106.

[0101] Among them, probability represents the possibility of an event occurring, and its value is between 0 and 1, including 0 and 1 itself. The track confidence determined in the embodiment of the present application is the probability that the track formed by the current detection point belongs to the track of the radar target. In the embodiment of the present application, if the sum is greater than or equal to the preset value, it means that the probability that the track formed by the current detection point belongs to the track of the radar target is relatively high. Therefore, the preset value can be set as needed, as long as the preset value is close to 1, for example, 0.9 or 1. In the implementation of the present application, preferably, the preset value is 1.

[0102] Step 3105: Determine the track confidence based on the sum value.

[0103] In the implementation of the present application, preferably, if the sum is less than or equal to a preset value, the sum is determined as the track confidence. In some embodiments, if the sum is small, the track confidence can also be directly determined as 0.

[0104] Step 3106: Determine the preset value as the track confidence.

[0105] In an embodiment of the present application, the weights corresponding to the first confidence, the second confidence, and the third confidence are obtained, and weighted accumulation is performed to obtain the final track confidence. Since the track confidence is determined from three different dimensions and the method of determining the track confidence by weighted accumulation is simple, the efficiency and accuracy of determining the track confidence are improved.

[0106] In some embodiments, the confidence corresponding to the maximum weight among the first weight, the second weight and the third weight can be directly determined as the track confidence, or the minimum confidence among the first confidence, the second confidence and the third confidence can be determined as the track confidence, or the maximum confidence among the first confidence, the second confidence and the third confidence can be determined as the track confidence.

[0107] Figure 5 FIG. 2 shows a schematic diagram of the structure of a device for determining the track confidence of a radar target provided in an embodiment of the present application. Figure 5 As shown, the device 400 includes: an acquisition module 401, a first determination module 402, a second determination module 403 and a third determination module 404. The acquisition module 401 is used to acquire the current detection point, the track estimation value and the track prediction value obtained by the radar detecting the radar target at the current moment, wherein the track estimation value is the position information of the radar target at the current moment estimated by the information of the current detection point, and the track prediction value is the position information of the radar target at the current moment predicted by the track of the radar target at the historical moment. The first determination module 402 is used to determine the first square value, wherein the first square value is the square value of the Mahalanobis distance between the track estimation value and the track prediction value. The second determination module 403 is used to determine the first confidence of the track of the radar target at the current moment formed by the current detection point from a preset data table according to the number of current detection points and the first square value, wherein the data table stores the corresponding relationship between the number of detection points and the square value of the Mahalanobis distance, and the corresponding relationship between the square value of the Mahalanobis distance and the first confidence. The third determination module 404 is used to determine the track confidence of the radar target according to the first confidence.

[0108] The device for determining the track confidence of a radar target provided in this embodiment is used to execute the technical solution of the method for determining the track confidence of a radar target in the aforementioned method embodiment. Its implementation principle and technical effect are similar and will not be described in detail here.

[0109] It is worth noting that the device for determining the track confidence of a radar target provided in this embodiment also includes other modules for executing the various steps of the above-mentioned method for determining the track confidence of a radar target, which will not be described one by one here.

[0110] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown, and the specific embodiment of the present application does not limit the specific implementation of the electronic device.

[0111] like Figure 6 As shown, the electronic device 500 may include: a processor 502 and a memory 504. The electronic device 500 may be a radar.

[0112] The memory 504 is used to store a computer program 506. The memory 504 may include a high-speed RAM memory, or may also include a non-volatile memory, such as at least one disk memory. The computer program 506 may include computer executable instructions.

[0113] The processor 502 is configured to execute the computer program 506 to implement the above-mentioned embodiment of the method for determining track confidence of a radar target.

[0114] The processor 502 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the track confidence determination device for a radar target may be processors of the same type, such as one or more CPUs; or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0115] An embodiment of the present application provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the embodiment of the method for determining the track confidence of the radar target described above is implemented.

[0116] An embodiment of the present application provides a computer program, which can be executed by a processor to implement the above-mentioned embodiment of the method for determining the track confidence of a radar target.

[0117] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the embodiment of the method for determining the track confidence of the radar target described above is implemented.

[0118] In several embodiments provided in the present application, if any function is implemented in the form of a software function module / unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the technical solution of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, server or other electronic device) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (RandomAccess Memory, RAM), disk or optical disk and other media that can store computer program codes.

[0119] The algorithm or display provided here are not inherently related to any specific computer, virtual system or other equipment. Various general systems can also be used together with the teaching based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present application described here, and the above description of specific languages ​​is to disclose the best mode of implementation of the present application.

[0120] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be constructed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In the claims that list several devices, several units or modules in these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

[0121] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining the track confidence of a radar target, characterized in that: The method comprises: Acquire a current detection point, a track estimation value, and a track prediction value obtained by detecting a radar target by the radar at the current moment, wherein the track estimation value is the position information of the radar target at the current moment estimated from the information of the current detection point, and the track prediction value is the position information of the radar target at the current moment obtained by predicting the track of the radar target at a historical moment; Determine a first square value, wherein the first square value is a square value of a Mahalanobis distance between the track estimation value and the track prediction value; Determining, from a preset data table, according to the number of the current detection points and the first square value, a first confidence level of the track of the radar target at the current moment formed by the current detection points, wherein the data table stores a corresponding relationship between the number of detection points and the square value of the Mahalanobis distance, and a corresponding relationship between the square value of the Mahalanobis distance and the first confidence level; The track confidence of the radar target is determined according to the first confidence.

2. The method according to claim 1, characterized in that The first square value is S q , determining, from a preset data table according to the number of the current detection points and the first square value, a first confidence level of the track of the radar target at the current moment formed by the current detection points, comprises: Determine the square values ​​of all Mahalanobis distances corresponding to the number of the current detection points in the data table; Determine the second square value S from the square values ​​of all Mahalanobis distances q ′ , wherein the S q and the S q The relationship between ′ satisfies S q >S q ′ and S q ≤S q ″,S q ′ and S q ″ is two adjacent square values ​​of all the square values ​​of the Mahalanobis distances sorted from small to large; The second square value S in the data table q The confidence level corresponding to ′ is determined as the first confidence level.

3. The method according to claim 1, characterized in that: Before determining the track confidence of the radar target according to the first confidence, the method further includes: Determine whether the number of the current detection points is greater than or equal to a preset threshold, wherein the preset threshold is related to the distance between the radar target and the radar at the current moment and the volume of the radar target; If the number of the current detection points is greater than or equal to the preset threshold, determining the first value as the second confidence of the track of the radar target at the current moment formed by the current detection points; If the number of the current detection points is less than the preset threshold, determining a second value according to the number of the current detection points and the preset threshold, and determining the second value as a second confidence level of the track of the radar target at the current moment formed by the current detection points, wherein the second value is less than the first value; Determining the track confidence of the radar target according to the first confidence includes: The track confidence is determined according to the first confidence and the second confidence.

4. The method according to claim 3, characterized in that Before determining the track confidence according to the first confidence and the second confidence, the method further includes: Obtaining a current update state value corresponding to the current moment and n historical update state values ​​corresponding to n historical moments, wherein the update state value corresponding to a certain moment is used to characterize the matching degree between the track prediction value and the track estimation value corresponding to the moment, and n is a positive integer; Determining a third confidence level according to the current update state value and the n historical update state values; Determining the track confidence according to the first confidence and the second confidence includes: The track confidence is determined according to the first confidence, the second confidence and the third confidence.

5. The method according to claim 4, characterized in that The determining a third confidence level according to the current update state value and the n historical update state values ​​comprises: Obtaining weights corresponding to the current moment and each of the historical moments respectively; The third confidence level is determined according to the weights corresponding to the current moment and each of the historical moments and the updated state values.

6. The method according to claim 5, characterized in that The n historical moments are the n historical moments closest to the current moment, the weights corresponding to the current moment are all greater than or equal to the weights corresponding to the n historical moments, and W i ≥W j , where W i and W j are the weights corresponding to the ith historical moment and the jth historical moment among the n historical moments, respectively, and the ith historical moment is later than the jth historical moment, i and j are both positive integers, i≤n, j≤n; The determining the third confidence level according to the weights and update status values ​​corresponding to the current moment and each of the historical moments includes: According to the formula Determine the third confidence level p3, where s l and pr l They are respectively the updated state value and the weight corresponding to the current moment and the lth moment among the n historical moments.

7. The method according to claim 4, characterized in that Determining the track confidence according to the first confidence, the second confidence and the third confidence includes: Obtaining a first weight, a second weight, and a third weight corresponding to the first confidence level, the second confidence level, and the third confidence level, respectively, wherein the sum of the first weight, the second weight, and the third weight is 1; The track confidence is determined according to the first confidence, the second confidence, the third confidence, the first weight, the second weight and the third weight.

8. The method according to claim 7, characterized in that Determining the track confidence according to the first confidence, the second confidence, the third confidence, the first weight, the second weight, and the third weight includes: respectively determining a first product of the first confidence and the first weight, a second product of the second confidence and the second weight, and a third product of the third confidence and the third weight; determining a sum of the first product, the second product, and the third product; Determine whether the sum is less than or equal to a preset value; If the sum is less than or equal to the preset value, determining the track confidence according to the sum; If the sum is greater than the preset value, the preset value is determined as the track confidence.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the method for determining track confidence of a radar target according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for determining the track confidence of a radar target described in any one of claims 1 to 8 is implemented.

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