A method and device for estimating the system error of two microwave over-the-horizon radars

Abstract

The present invention discloses a method and device for estimating the system error of two microwave over-the-horizon radars, comprising the following steps: step 1, based on polar coordinate measurement values, selecting the track points of the two microwave over-the-horizon radars; step 2, based on the selected track points, calculating the distance matrix, and performing track pairing of the two microwave over-the-horizon radars; step 3, based on the pairing result, using a particle swarm optimization method to estimate the system error of the two microwave over-the-horizon radars. The present invention uses the Vicente formula to estimate the geographic coordinate measurement value of the target for an over-the-horizon sea surface target, thereby improving the accuracy of the system error estimation.

Description

Technical Field

[0001] The invention relates to the field of microwave over-the-horizon radar network detection, and in particular to a method and a device for estimating system errors of two microwave over-the-horizon radars. Background Art

[0002] In order to improve the performance of multi-radar tracking when multiple radars are networked, it is usually necessary to first estimate the system errors such as ranging and direction finding of each radar.

[0003] Conventional radar uses electromagnetic waves to propagate along a nearly straight line to detect targets within the line of sight. When estimating the system error of multi-radar networking data processing, algorithms such as real-time quality control algorithm, least squares estimation algorithm, generalized least squares algorithm, exact maximum likelihood algorithm, and generalized least squares algorithm based on ECEF coordinate system can use matrix translation and rotation operations to perform coordinate transformation and use formulas to directly estimate the system error.

[0004] Unlike conventional radars, microwave over-the-horizon radars use the super-refractive effect of the sea surface atmosphere. Electromagnetic waves can propagate in the sea surface atmospheric waveguide in a great circle path close to that formed by the curvature of the earth. Generally, they can detect various types of surface targets at a distance of tens to hundreds of kilometers. The propagation of electromagnetic waves along the great circle path is affected by many factors such as temperature, humidity, wind direction, and air pressure, and there is a certain error in the radar's distance measurement of the target.

[0005] For targets hundreds of kilometers away, based on the assumption that electromagnetic waves propagate along a nearly straight line, using matrix translation and rotation operations to transform coordinates will introduce large errors. Therefore, it is necessary to provide a method for estimating the error of two microwave over-the-horizon radar systems with small errors. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a method and device for estimating the system error of two microwave over-the-horizon radars, thereby improving the accuracy of system error estimation.

[0007] In order to solve the above technical problems, the technical solution of the present invention is:

[0008] A method for estimating the system error of two microwave over-the-horizon radars comprises the steps of:

[0009] Step 1, based on the polar coordinate measurement values, selecting the track points of two microwave over-the-horizon radars;

[0010] Step 2, calculating the distance matrix based on the screened track points, and performing track pairing of the two microwave over-the-horizon radars;

[0011] Step 3: Based on the pairing results, the particle swarm optimization method is used to estimate the system errors of the two microwave over-the-horizon radars.

[0012] Furthermore, the screening of the track points of the two microwave over-the-horizon radars specifically includes:

[0013] Step 1-1, take radar i as the origin of the rectangular coordinate system, and Track points Convert from polar coordinates to rectangular coordinates to obtain rectangular measurements , Indicates time, Indicates direction, Indicates distance, represents the horizontal axis, represents the vertical coordinate, , , is the number of tracks;

[0014] Step 1-2: Convert the rectangular coordinate measurement values ​​into time Sort from small to large and group them;

[0015] Steps 1-3, perform linear fitting in each group and convert the fitted values ​​into polar coordinate measurements;

[0016] Step 1-4, determine whether the polar coordinate measurement value in each group meets the conditions. If the polar coordinate measurement value does not meet the conditions, discard all track points in the group.

[0017] Furthermore, when grouping in step 1-2, if the last group is insufficient If there are no measurement values, the group is discarded and P is the measurement value of each group.

[0018] Furthermore, the steps 1-3 specifically include: Perform linear fitting and obtain the fitting value ,right Perform linear fitting and obtain the fitting value ; The fitted value Convert to polar coordinates ,in Indicates the position after conversion. Represents the distance after conversion.

[0019] Furthermore, the steps 1-4 specifically include: calculating in each group , ;if or , then discard all the track points in the group, where and Respectively represent radar The nominal accuracy of the azimuth and distance measurements, After selecting the track points, the radar No. The track points of the track are recorded as .

[0020] Furthermore, the step 2 specifically includes:

[0021] For Radar 1 Tracks and radar 2 Tracks, definition , , is the minimum value of the scanning period of the two radar antennas; at time Radar 1 The tracks are respectively , Linear interpolation, get the interpolated rectangular coordinates ; at the time Radar 2 The tracks are respectively , Linear interpolation, get the interpolated rectangular coordinates ;

[0022] Convert the interpolated rectangular coordinates to polar coordinates and convert to geographic coordinates using Vicente's formula;

[0023] Computational Radar 1 Tracks and radar 2 The distance between the tracks , determine the correlation matrix ;

[0024] Correlation Matrix Using the global nearest neighbor association algorithm, the polar coordinate measurement values ​​of the two radar pairs are obtained, which are recorded as ,in, , and Indicates the radar 1 bearing measurements and distance measurements, and Indicates the radar 2 bearing measurements and distance measurements.

[0025] Furthermore, the For: If or , ,otherwise, , where the parameters , is the upper limit of the longitude difference between two different target tracks. The upper limit of the latitude difference between two different target tracks is set. and Indicates the longitude and latitude of radar 1 converted using Vicente's formula. and Indicates the longitude and latitude converted by Radar 2 using Vicente's formula.

[0026] Furthermore, the particle swarm optimization method in step 3 A particle is a vector with 10 components , respectively represent the longitude error, latitude error, azimuth error, zero-order term of distance error, and first-order term of distance error of radar 1, and the longitude error, latitude error, azimuth error, zero-order term of distance error, and first-order term of distance error of radar 2; particle Use Vicente's formula to convert paired polar measurements to geographic coordinates:

[0027] ; ;

[0028] Among them, the symbol Indicates the use of Vicente function, and Indicates radar The longitude and latitude measurements, and Indicates radar No. The longitude and latitude are calculated from the polar coordinate measurements using the Vicente formula.

[0029] Furthermore, the particles of the particle swarm optimization method in step 3 The fitness value is designed to be:

[0030] ;

[0031] Among them, the parameters .

[0032] A device for estimating the system error of two microwave over-the-horizon radars, comprising:

[0033] Track point screening unit, based on polar coordinate measurement values, screens the track points of two microwave over-the-horizon radars;

[0034] The track matching unit calculates the distance matrix based on the selected track points and matches the tracks of two microwave over-the-horizon radars;

[0035] The system error estimation unit estimates the system errors of the two microwave over-the-horizon radars based on the pairing results using the particle swarm optimization method.

[0036] Compared with the prior art, the beneficial effects of the present invention include:

[0037] (1) Based on track point screening and track pairing, the present invention obtains polar coordinate observation values ​​of two microwave over-the-horizon radars simultaneously detecting the same target, and uses the Vicente formula based on the iteration method in the particle swarm optimization algorithm to establish the fitness function, thereby improving the accuracy of system error estimation;

[0038] (2) Considering multiple system error factors, an objective function is established in geographic space, and the particle swarm optimization method is used to obtain multiple system error parameters of the two radars. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the processing flow of the present invention.

[0040] Figure 2 It is the error curve diagram of calculating geographic coordinates by Vicente formula of the present application and traditional method. DETAILED DESCRIPTION

[0041] The present invention will be further described below in conjunction with the accompanying drawings and embodiments. Figure 1 As shown, a method for estimating the system error of two microwave over-the-horizon radars includes:

[0042] 1. Filtering track points

[0043] Defining radar No. The track points of the track are ,in , , , Indicates time, , Indicates direction, Indicates distance; radar As the origin of the rectangular coordinate system, the track point Convert from polar coordinates to rectangular coordinates to obtain rectangular measurements ,in represents the horizontal axis, Represents the ordinate; the rectangular coordinate measurement value By time Sort from small to large and group them; each group contains 64 measurement values, and the grouping rule is , , , In the first group, , , , In the second group, and so on, if the last group has less than 64 measurement values, this group will be discarded; Perform linear fitting and obtain the fitting value ,right Perform linear fitting and obtain the fitting value ; The fitted value Convert to polar coordinates ,in Indicates direction, Represents distance; calculated within each group , ;if or , then discard all the track points in the group; after filtering the track points, the radar No. The track points of the track are recorded as ,in Indicates time, , Indicates direction, Indicates distance, represents the abscissa of the rectangular coordinate system, Represents the ordinate of the rectangular coordinate system.

[0044] (II) Calculate the distance matrix and perform track pairing

[0045] For over-the-horizon targets hundreds of kilometers away, the Vicente formula based on iteration can be used to convert polar coordinates into high-precision geographic coordinates. For distances ranging from a few centimeters to nearly 20,000 kilometers, the distance accuracy is at the millimeter level, and the accuracy of the azimuth angle is one ten-thousandth of a second.

[0046] Set time is the minimum value of the scanning period of the two radar antennas; for radar 1 Tracks and radar 2 Tracks, definition , ; at the time Radar 1 The tracks are respectively , Linear interpolation, where , get the interpolated rectangular coordinates , and then converted to polar coordinates , converted to geographic coordinates using Vicente's formula ,in , and represent the horizontal and vertical coordinates respectively, and Represents direction and distance respectively. and Represent longitude and latitude respectively; at time Radar 2 The tracks are respectively , Linear interpolation, get the interpolated rectangular coordinates , and then converted to polar coordinates , converted to geographic coordinates using Vicente's formula ,in , and represent the horizontal and vertical coordinates respectively, and Represents direction and distance respectively. and Respectively represent longitude and latitude; For Radar 1 Tracks and radar 2 The distance between the tracks, such as or , ,otherwise, ,in ; For the correlation matrix Using the global nearest neighbor association algorithm, the polar coordinate measurement values ​​of the two radar pairs are obtained, which are recorded as ,in , and Indicates the radar 1 bearing measurements and distance measurements, and Indicates the radar 2 bearing measurements and distance measurements.

[0047] 3. Estimating the System Error of Two Radars Using Particle Swarm Optimization

[0048] In the particle swarm algorithm, the A particle is a vector with 10 components , respectively represent the longitude error, latitude error, azimuth error, zero-order term of distance error, and first-order term of distance error of radar 1, and the longitude error, latitude error, azimuth error, zero-order term of distance error, and first-order term of distance error of radar 2; particle position The value range of each component is , ; If a certain error of the radar can be ignored, the particle position The corresponding amount The value range of Set to 0; for particles Convert paired polar measurements to geographic coordinates using Vicente's formula , ,symbol Indicates that the calculation is performed using Vicente's formula. and Indicates radar The longitude and latitude measurements, and Indicates radar No. The longitude and latitude of the particle are calculated by the Vicente formula. The fitness value is ,in .

[0049] In the simulation experiment, the longitude of the microwave over-the-horizon radar was set to 129.5 degrees and the latitude was set to 27.5 degrees. Six targets were set on the sea surface with azimuths of 90 degrees and distances of 50, 100, 200, 400, 600, and 800 kilometers respectively. The longitude and latitude of the target were calculated using the Vicente formula and the traditional matrix translation and rotation operations. The formula Calculate the error of the two methods, where Calculate the error of geographic coordinates, the result is as follows Figure 2 ,from Figure 2 It can be seen that the greater the distance between the sea surface target and the radar, the greater the error in calculating the geographic coordinates by the two methods, and the error in the geographic coordinates increases much faster than the distance.

[0050] Set the longitude and latitude system errors of radar 1 to 0, the azimuth system error to 0.25 degrees, and the distance system error to -500 meters. Set the longitude and latitude system errors of radar 2 to 0, the azimuth system error to -0.2 degrees, and the distance system error to 800 meters. Set the number of particles to 1000, and the value range of each particle component to , the value range of each error is set to [0,0,0.5,1000,0,0,0,0.5,1000,0] respectively.

[0051] Table 1 is part of the information printed during a calculation using the particle swarm algorithm. After 438 iterations, the fitness function value dropped from the initial 230.501 to 0.022. The estimated azimuth system error of radar 1 was 0.247 degrees, and the 0th order term of the distance system error was -413.431 meters. The azimuth system error of radar 2 was -0.202 degrees, and the 0th order term of the distance system error was 894.843 meters. The difference between the estimated value of the azimuth system error of the two radars and the set error value is less than 0.01 degrees, and the difference between the estimated value of the distance system error and the set error value is less than 100 meters, which meets the needs of multi-radar networking.

[0052] Table 1 Printing information during a simulation calculation

[0053]

[0054] This embodiment also provides a device for estimating system errors of two microwave over-the-horizon radars, including:

[0055] Track point screening unit, based on polar coordinate measurement values, screens the track points of two microwave over-the-horizon radars;

[0056] The track matching unit calculates the distance matrix based on the selected track points and matches the tracks of two microwave over-the-horizon radars;

[0057] The system error estimation unit estimates the system errors of the two microwave over-the-horizon radars based on the pairing results using the particle swarm optimization method.

[0058] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for estimating the system error of two microwave over-the-horizon radars, characterized in that: Includes steps: Step 1, based on the polar coordinate measurement values, selecting the track points of two microwave over-the-horizon radars; Step 2, calculating the distance matrix based on the screened track points, and performing track pairing of the two microwave over-the-horizon radars; Step 3, based on the pairing results, the particle swarm optimization method is used to estimate the system errors of the two microwave over-the-horizon radars; The step 2 specifically includes: For Radar 1 Tracks and radar 2 Tracks, definition , , is the minimum value of the scanning period of the two radar antennas; at time Radar 1 The tracks are respectively , Linear interpolation, get the interpolated rectangular coordinates ; at the time Radar 2 The tracks are respectively , Linear interpolation, get the interpolated rectangular coordinates ,in, represents the time of the jth track point in the pth track of radar i, represents the time of the jth track point in the qth track of radar i, , represents the horizontal and vertical coordinates of the jth track point in the pth track of radar i, , represents the horizontal and vertical coordinates of the jth track point in the qth track of radar i, , , ; Convert the interpolated rectangular coordinates to polar coordinates and convert to geographic coordinates using Vicente's formula; Computational Radar 1 Tracks and radar 2 The distance between the tracks , determine the correlation matrix ; Correlation Matrix Using the global nearest neighbor association algorithm, the polar coordinate measurement values ​​of the two radar pairs are obtained, which are recorded as ,in, , and Indicates the radar 1 bearing measurements and distance measurements, and Indicates the radar 2 bearing measurements and distance measurements; Said For: If or , ,otherwise, , where the parameters , is the upper limit of the longitude difference between two different target tracks. The upper limit of the latitude difference between two different target tracks is set. and Indicates the longitude and latitude of radar 1 converted using Vicente's formula. and Indicates the longitude and latitude converted by Radar 2 using Vicente's formula; The particle swarm optimization method in step 3 A particle is a vector with 10 components , respectively represent the longitude error, latitude error, azimuth error, zero-order term of distance error, and first-order term of distance error of radar 1, and the longitude error, latitude error, azimuth error, zero-order term of distance error, and first-order term of distance error of radar 2; particle Use Vicente's formula to convert paired polar measurements to geographic coordinates: ； ； Among them, the symbol Indicates the use of Vicente function, and Indicates radar The longitude and latitude measurements, and Indicates radar No. The longitude and latitude of the polar coordinate measurements calculated using the Vicente formula; Particles of the particle swarm optimization method in step 3 The fitness value is designed to be: ； Among them, the parameters .

2. A method for estimating the system error of two microwave over-the-horizon radars according to claim 1, characterized in that: The selection of the track points of the two microwave over-the-horizon radars specifically includes: Step 1-1, take radar i as the origin of the rectangular coordinate system, and Track points Convert from polar coordinates to rectangular coordinates to obtain rectangular measurements , Indicates time, Indicates direction, Indicates distance, represents the horizontal axis, represents the vertical coordinate, , , is the number of tracks; Step 1-2: Convert the rectangular coordinate measurement values ​​into time Sort from small to large and group them; Steps 1-3, perform linear fitting in each group and convert the fitted values ​​into polar coordinate measurements; Step 1-4, determine whether the polar coordinate measurement value in each group meets the conditions. If the polar coordinate measurement value does not meet the conditions, discard all track points in the group.

3. A method for estimating the system error of two microwave over-the-horizon radars according to claim 2, characterized in that: When grouping in step 1-2, if the last group is insufficient If there are no measurement values, the group is discarded and P is the measurement value of each group.

4. A method for estimating the system error of two microwave over-the-horizon radars according to claim 2, characterized in that: The steps 1-3 specifically include: Perform linear fitting and obtain the fitting value ,right Perform linear fitting and obtain the fitting value ; The fitted value Convert to polar coordinates ,in Indicates the position after conversion. Represents the distance after conversion.

5. A method for estimating the system error of two microwave over-the-horizon radars according to claim 3, characterized in that: The steps 1-4 specifically include: calculating in each group , ;if or , then discard all the track points in the group, where and Respectively represent radar The nominal accuracy of the azimuth and distance measurements, After selecting the track points, the radar No. The track points of the track are recorded as .

6. A device for estimating the system error of two microwave over-the-horizon radars based on the method described in any one of claims 1 to 5, characterized in that: include: Track point screening unit, based on polar coordinate measurement values, screens the track points of two microwave over-the-horizon radars; The track matching unit calculates the distance matrix based on the selected track points and matches the tracks of two microwave over-the-horizon radars; The system error estimation unit estimates the system errors of the two microwave over-the-horizon radars based on the pairing results using the particle swarm optimization method.

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