A Dual-Station Passive Localization and Target Identification Method

Abstract

This invention belongs to the field of radar technology, specifically relating to a dual-station passive positioning and target identification method. The method involves: acquiring radar coordinates; transforming the measured angles of each node radar in the northeast-sky coordinate system to a unified rectangular coordinate system referenced by the northeast-sky coordinate system of the first node radar; establishing four measurement parameter equations based on the triangulation formula, and randomly selecting three equations as a set of measurement subsets, through which the target position can be calculated; transforming the angle errors of each node radar in the northeast-sky coordinate system into angle errors in the unified rectangular coordinate system, and then obtaining the angle error covariance matrix; calculating the covariance matrix of the target position vector difference and its Mahalanobis distance based on the target positions obtained from different subsets, and performing hypothesis testing on the target based on the characteristic that Mahalanobis distance follows a chi-square distribution; and determining whether the target is a real target by comparing the Mahalanobis distances of different points, effectively eliminating false intersections.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of radar, and particularly relates to a bistatic passive positioning and target identification method. BACKGROUND

[0002] In modern warfare, radars are facing more and more threats, such as anti-radiation missiles and electronic jamming. In order to improve the survival and working efficiency of radars, researchers have developed and researched many innovative radar systems and technologies. Among them, passive radars are considered as a very potential solution. Direction finding cross positioning technology, as a mature technology in passive radars, has been widely used. However, when multiple stations are used to cross locate the monitoring area where there are two or more targets, the intersection of different direction finding lines will produce a large number of false positioning points. These false points seriously affect the accuracy and running speed of the radar.

[0003] In order to quickly and effectively eliminate false points, the main method proposed at home and abroad is to add one or more base stations on the basis of bistatic positioning, and use multi-line intersection points and clustering algorithm to eliminate false targets. This method can effectively eliminate false targets. In the case of using only bistatic positioning, people still have no good way to eliminate false targets obtained by bistatic direction finding cross positioning.

[0004] The false point elimination method based on Mahalanobis distance proposed in this paper is a false point elimination method based on bistatic direction finding cross positioning. By comparing the Mahalanobis distances of different points, it is judged whether the target is a false point, which can effectively eliminate false targets. SUMMARY

[0005] The purpose of the application is to provide a bistatic passive positioning and target identification method, which is a false point elimination method based on bistatic direction finding cross positioning. By comparing the Mahalanobis distances of different points, it is judged whether the target is a false point, which can effectively eliminate false targets.

[0006] The technical scheme adopted by the application is as follows:

[0007] A bistatic passive positioning and target identification method comprises the following steps:

[0008] Step 1: Obtain the radar coordinates, and transform the measured angles of each node radar in the northeast celestial coordinate system into a unified rectangular coordinate system with the first node radar northeast celestial coordinate system as the reference;

[0009] Step 2: According to the triangular positioning formula, four measurement parameter equations are established, and three equations are selected as a measurement subset, and the target position can be calculated through the subset;

[0010] Step 3: convert the angle error of each node radar in the northeast coordinate system into the angle error in the unified coordinate system, and then obtain the angle error covariance matrix;

[0011] Step 4: calculate the covariance matrix of the target position vector difference and the Mahalanobis distance according to the target positions obtained by different subsets, and perform hypothesis testing on the target according to the characteristic that the Mahalanobis distance obeys chi-square distribution;

[0012] Step 5: determine whether the target is a real target according to the hypothesis test result obtained in step 4.

[0013] The technical effects obtained by the present application are:

[0014] The present application is based on the angle measurement information of the dual-station radar redundancy, two positioning results of the same target are obtained through different measurement sets, and whether the target is a real target is determined by comparing the Mahalanobis distance of the two positioning results, so that the false target can be effectively eliminated. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is the implementation flowchart of the present application;

[0016] Figure 2 is the radar layout and target information example diagram of the present application;

[0017] Figure 3 is the real target 1 discrimination probability diagram of the present application.

[0018] Figure 4 is the real target 2 discrimination probability diagram of the present application.

[0019] Figure 5 is the false target discrimination probability diagram of the present application. DETAILED DESCRIPTION

[0020] In order to make the purpose and advantages of the present application clearer and more apparent, the present application will be specifically described below in combination with embodiments. It should be understood that the following text is only used to describe one or several specific embodiments of the present application, and does not strictly limit the specific protection scope requested by the present application.

[0021] As shown in Figure 1 , a dual-station passive positioning and target discrimination method comprises the following steps:

[0022] Step 1: obtain the radar coordinates, and convert the measurement angle of each node radar in the northeast coordinate system into the unified angle coordinate system with the first node radar northeast coordinate system as the reference;

[0023] Specifically, the step 1 comprises the following steps:

[0024] Step 101: In the latitude, longitude, and altitude coordinate system, set the first radar coordinates as (L1, B1, H1) and the second radar coordinates as (L2, B2, H2), where L... k B k and H k These are the longitude, latitude, and altitude of the k-th radar station, respectively.

[0025] Step 102: The target angle measurement set obtained by the first radar is Θ1, and the target angle measurement set obtained by the second radar is Θ2;

[0026] Θ1={(α1,β1),(α2,β2),…,(α N ,β N )}

[0027] Θ2={(α1′,β1′),(α2′,β2′),…,(α′ N ,β′ N )}

[0028] Among them, (α) i ,β i ) represents the azimuth and elevation angles corresponding to target i measured by the first radar; (α) i ′,β i ′) represents the azimuth and elevation angles of target i measured by the second radar.

[0029] Step 103: Based on the angle measurement set in Step 102, set the target-to-radar distance r, and calculate the coordinates of each target in the northeast-northeast coordinate system centered on the radar;

[0030] Step 104: Assume the latitude and longitude of the reference point is (L r B r The coordinates of the reference point in the Earth-centered Earth-fixed coordinate system are P. r =(X r ,Y r Z r The target's coordinates in the Earth-centered Earth-fixed coordinate system are P = (X, Y, Z), and its coordinates in the Northeast-Sky coordinate system with the reference point as the origin are l = (e, n, u). Therefore, the coordinate transformation formula is:

[0031] l = A(PP) r )

[0032] Where A is the coordinate rotation matrix.

[0033]

[0034] Step 105: Assume the distance from target i to radar station 2 is r. iGiven the azimuth and elevation angles of target i in the northeast-northeast coordinate system of radar station 2, we can obtain the coordinates of target i in the northeast-northeast coordinate system of radar station 2 as follows:

[0035]

[0036] Step 106: The coordinates of target i in the northeast-northeast coordinate system of radar station 2 (X) enu2 The coordinates of radar station 1 in the northeast celestial coordinate system are converted to X. enu1

[0037]

[0038] Where A1 and A2 are rotation matrices with the first node radar as the reference point and the second node radar as the reference point, respectively, and P1 and P2 are the coordinates of the first node radar and the second node radar in the geocentric coordinate system.

[0039] Step 107: The angle information of target i relative to radar station 2 in the northeast-northeast coordinate system of radar station 1 is (α″). i ,β″ i )

[0040]

[0041] Where X2 = [x2, y2, z2] T The coordinates of radar station 2 in the northeast-northeast coordinate system of radar station 1 are given, with the superscript T indicating transpose.

[0042] Step 2: Based on the triangulation formula, establish four measurement parameter equations. Randomly select any three equations as a measurement subset. The target position can be calculated through the subset.

[0043] Specifically, step 2 includes the following steps:

[0044] Step 201: Under the unified rectangular coordinate system of radar station 1 (northeast-east celestial coordinate system), the coordinates of radar 1 are X1 = [0,0,0]. T The coordinates of radar station 2 are X2 = [x2, y2, z2]. T Let the target coordinates be X = [x, y, z] T The target's azimuth and elevation angles relative to radar 1 are α1 and β1, respectively; the azimuth and elevation angles relative to radar 1 are α″1 and β″1, respectively, with the azimuth angle positive at east-northeast.

[0045] Based on the triangulation geometry, four measurement parameter equations are established for α1, β1, α″1, and β″1; any three equations are randomly selected to solve for the target position parameter X = [x, y, z]. T ;

[0046]

[0047] Step 3: Transform the angle error of each node radar in the northeast-north-sky coordinate system into the angle error in a unified rectangular coordinate system, and then obtain the angle error covariance matrix;

[0048] Furthermore, step 3 includes the following steps:

[0049] Step 301: From steps 107, 106, and 105, we can obtain the angle error [dα″] of target i relative to radar station 2 in the northeast-northeast coordinate system of radar station 1. i ,dβ″ i ] T

[0050] [dα″ i ,dβ″ i ] T =K1[dα′ i ,dβ′ i ] T

[0051] Where K1 is the transformation matrix from the radar 2 northeast-sky angle measurement error to the radar 1 northeast-sky angle measurement error, [dx, dy, dy] T The error in the northeast zenith angle measurement of Radar 2;

[0052] Step 302: The angular error covariance matrix of the two radar stations in the northeast-north-sky coordinate system of radar station 1 is D;

[0053]

[0054] in, in These are the variances of the angle measurement errors for the azimuth and elevation angles of the two radars, respectively. Let I be the transformation matrix for the angle error. 2×2 It is a 2×2 identity matrix, 0 2×2 It is a 2×2 zero matrix.

[0055] Step 4: Based on the target positions obtained from different subsets, calculate the covariance matrix of the target position vector difference and its Mahalanobis distance, and perform hypothesis testing on the target based on the characteristic that the Mahalanobis distance follows a chi-square distribution;

[0056] Furthermore, step 4 includes the following steps:

[0057] Step 401: Obtain the actual target position X from the measurement parameter equations ①, ②, and ③ in step 201. Its partial derivative error is...

[0058] dX=T1[dα i ,dβ i,dα″ i ,dβ″ i ] T

[0059] Wherein, T1 is the error transfer matrix for positioning based on the measurement parameter equations ①, ②, and ③;

[0060] Step 402: Obtain the actual target position Y from the measurement parameter equations ①, ③, and ④, with the partial derivative error being...

[0061] dY=T2[dα i ,dβ i ,dα″ i ,dβ″ i ] T

[0062] Wherein, T2 is the error transfer matrix for positioning based on the measurement parameter equations ①, ③, and ④;

[0063] Step 403: Solve for the error covariance matrix Σ of the vector difference between the two positions Δ = XY;

[0064] Σ=E[(dX-dY)(dX-dY) T ];

[0065] Step 404: Calculate the Mahalanobis distance d between the two measurements based on the position difference Δ = XY and the error covariance matrix Σ;

[0066] d = (XY) T Σ -1 (XY)

[0067] Step 405: Based on step 404, since the x and y values ​​obtained from the two sets of measurement subsets are the same, the Mahalanobis distance is simplified to... At this point, z1 represents the target z-coordinate calculated from the first set of measurement subsets, and z2 represents the target z-coordinate calculated from the second set of measurement subsets. Let Σ represent the inverse of the data in the i-th row and j-th column of the error covariance matrix Σ.

[0068] Step 406: Based on the fact that the Mahalanobis distance approximately follows the χ² value... 2 The distribution is used to perform hypothesis testing on the real target and eliminate false target information.

[0069]

[0070] Wherein, the threshold η is determined by the significance level α of the test, where α is the preset false positive probability of the true target.

[0071] Step 5: Based on the hypothesis test results obtained in Step 4, determine whether the target is a real target.

[0072] To more clearly illustrate the effects of the present invention, the following simulation experiments are disclosed herein;

[0073] Experimental Scenario: In a latitude-longitude coordinate system, the coordinates of the two radars are (34°, 35°, 100m) and (34.72°, 35°, 603.5m), respectively. In the simulation scenario, the trajectory of the first real target changes as follows: longitude from 34.44° to 34.53°, latitude from 35.75° to 35.86°, and altitude from 50.67km to 60.87km. The trajectory of the second real target changes as follows: longitude from 34.35° to 34.26°, latitude from 35.538° to 35.537°, and altitude from 60.42km to 65.36km. The angular measurement error of both radars is 0.1 radians.

[0074] Experimental content: The position of the target trajectory is calculated. Each target has 100 points. The false target is obtained by bi-station direction finding cross-positioning. Under the condition that the false target misjudgment probability is 0.0001, 100,000 Monte Carlo simulation experiments are carried out to obtain the probability of distinguishing between true and false targets.

[0075] Experimental results:

[0076] The probability of identifying the first real target is as follows: Figure 3 As shown, the probability of identifying the second true target is as follows: Figure 4 As shown, the probability of identifying false targets is as follows: Figure 5 As shown in the simulation diagram, this method can effectively distinguish between real and fake targets.

[0077] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A method of bistatic passive location and target discrimination, the method comprising: The method comprises the following steps: ​ Step 1: obtaining radar coordinates, transforming the measurement angle of each node radar in the northeast celestial coordinate system of the first node radar to a unified rectangular coordinate system with the northeast celestial coordinate system of the first node radar as a reference; Step 2: establishing four measurement parameter equations according to a triangular positioning formula, selecting three equations as a measurement subset, and calculating the target position through the subset; The step 2 of calculating the target position according to the triangular positioning formula comprises the following steps: Step 201: In a straight angle coordinate system with radar 1 northeast coordinate system as the unit, the radar 1 coordinate is , the radar 2 coordinate is , the target coordinate is assumed to be , the azimuth and elevation angles of the target relative to radar 1 are and respectively; the azimuth and elevation angles of the target relative to radar 2 are and respectively, and the azimuth angle is positive to the east and north. According to the triangle positioning geometry, for and Four measurement parameter equations are established; optional 3 equations, solve the target position parameters ; ； Step 3: converting the angle error of each node radar in the northeast celestial coordinate system into the angle error in the unified rectangular coordinate system, and then obtaining an angle error covariance matrix; Step 4: calculating the covariance matrix of the target position vector difference and the Mahalanobis distance according to the target positions obtained by different subsets, and performing hypothesis testing on the target according to the characteristic that the Mahalanobis distance obeys chi-square distribution; Step 5: judging whether the target is a real target according to the hypothesis testing result obtained in step 4.

2. The method of claim 1, wherein: The step 1 of transforming the northeast celestial coordinate system with each node radar as a reference origin to the unified rectangular coordinate system with the northeast celestial coordinate system of the first node radar as a reference comprises the following steps: Step 101: In the latitude, longitude, and altitude coordinate system, set the first radar coordinates as follows: The second radar coordinates are ,in , and The first The longitude, latitude, and altitude of each radar; Step 102: Each target angle measurement set measured by the first radar is , and each target angle measurement set measured by the second radar is ; ； wherein, represents a target measured by the 1st radar the corresponding azimuth and elevation angles; represents a target measured by the 2nd radar the corresponding azimuth and elevation angles; Step 103: setting the distance r of the target to the radar, and calculating the coordinates of each target in the northeast celestial coordinate system with the radar as a center according to the angle measurement set in step 102; Step 104: assuming the longitude and latitude of the reference point are , the coordinates of the reference point in the geocentric and terrestrial coordinate system are , the coordinates of the target in the geocentric and terrestrial coordinate system are , and the coordinates of the target in the north-eastern celestial coordinate system with the reference point as the origin are ; then the coordinate system conversion formula is: ； Wherein, A is a coordinate rotation matrix ； Step 105: Assuming the target is at a distance of , from the radar 2 , the azimuth and elevation angles of the target in the radar 2 northeast sky coordinate system, the coordinates of the target in the radar 2 northeast sky coordinate system are ； Step 106: Target Coordinates of radar 2 in the northeast celestial coordinate system Convert the coordinates of radar 1 in the northeast celestial coordinate system to ； wherein, and R1and R2are rotation matrices when the 1st node radar and the 2nd node radar are taken as reference points, respectively, and X1and X2are coordinates of the 1st node radar and the 2nd node radar in the ECF coordinate system, respectively. Step 107: Target The angle information of radar 1 relative to radar 2 in the northeast celestial coordinate system of radar 1 is ； wherein is the coordinate of radar 2 in the radar 1 northeast celestial coordinate system, with superscript T denoting the transpose.

3. The method of claim 1, wherein: The step 3 of converting the angle error of each node radar in the northeast celestial coordinate system into the angle error in the unified rectangular coordinate system to obtain the angle error covariance matrix comprises the following steps: Step 301: From steps 107, 106 and 105, the target Error in radar 1 northeast celestial coordinate system relative to radar 2 angle ； wherein, is a conversion matrix of radar 2 northeast sky angle measurement errors to radar 1 northeast sky angle measurement errors; Step 302: The angle error covariance matrix of two radars in the radar 1 northeast sky coordinate system is ; ； wherein ; wherein are the variance of the angle measurement errors of the azimuth and elevation angles, respectively; is the transformation matrix of the angle errors, is is the identity matrix, is is the zero matrix.

4. The method of claim 1, wherein: The step 4 of calculating the covariance matrix of the target position vector difference and the Mahalanobis distance, and performing hypothesis testing on the target according to the characteristic that the Mahalanobis distance obeys chi-square distribution comprises the following steps: Step 401: Obtain the target actual position from the parameter measurement equations ①, ②, ③ in step 201 with partial derivative error ； wherein is the error transfer matrix for the parameter measurement equations ①, ②, ③ Step 402: Obtain the target actual position from the measurement parameter equations ①, ③, ④ with partial derivative error ； wherein is the error transfer matrix for the parameter measurement equations ①, ③, ④ Step 403: Solving the difference of two position vectors error covariance matrix ; ； Step 404: Based on the position difference And error covariance matrix The Mahalanobis distance between the two measurements was calculated. ; ； Step 405: Based on step 404, the solution obtained from the two sets of measurement subsets... and Similarly, the Mahalanobis distance simplifies to ,at this time Indicates the objective of solving the first set of measurement subsets. coordinate, Indicates the objective of solving the second set of measurement subsets. coordinate, Represents the error covariance matrix No. Line number Reverse the column data; Step 406: According to the Mahalanobis distance approximation to obey distribution, according to which the real target is tested for hypothesis, and false target information is removed; ； wherein the threshold is determined by a significance level of the test, i.e. a preset false target probability, and the threshold 。

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