Anti-multipath radar angle measurement system and method based on comprehensive angle measurement

Abstract

The invention relates to radar angle measurement, in particular to an anti-multipath radar angle measurement system and method based on comprehensive angle measurement, and the method comprises the steps: an angle measurement fusion module generates multi-source pitch angle candidate data through sum-difference angle measurement and sum-sum angle measurement; the track batch optimization module is used for performing batch processing on the multi-source pitch angle candidate data of the multiple trace points in a track batch stage, selecting an optimal pitch angle and updating the three-dimensional coordinates of each trace point; the track association optimization module is used for calculating the Euclidean distance between the three-dimensional coordinate corresponding to the multi-source pitch angle candidate data of each trace point and the historical track in the track tracking stage, selecting the optimal pitch angle and updating the three-dimensional coordinate of each trace point; the flight path smoothing processing module is used for smoothing the flight path height sequence and outputting the smoothed flight path height sequence so as to reduce noise interference and improve height estimation stability; the technical scheme provided by the invention can effectively overcome the defects that multipath interference is difficult to suppress effectively, the angle measurement precision is low and the track starting stability is poor.

Description

Technical Field

[0001] This invention relates to radar angle measurement, and more specifically to an anti-multipath radar angle measurement system and method based on integrated angle measurement. Background Technology

[0002] In radar detection systems, angle measurement accuracy directly affects the reliability of target localization and track tracking. Traditional radars widely employ the sum-difference angle measurement method for elevation angle measurement. While this method offers advantages such as high sensitivity and real-time performance, the amplitude and phase of the difference signal are easily distorted under the influence of multipath effects, leading to a "jump" phenomenon in angle estimation that deviates significantly from the true target angle. This multipath interference is particularly pronounced at long ranges, not only increasing altitude measurement errors but also causing track launch failures, severely impacting the operational effectiveness of the radar system.

[0003] Among existing improvement schemes, some employ a combination of angle measurement and beamwidth methods to enhance stability in multipath environments. However, the resolution of this method is limited by the number and width of beams, resulting in high algorithm complexity when tracking dynamic targets. Meanwhile, some schemes rely solely on a single improved algorithm to optimize angle measurement results, failing to fully utilize the complementary characteristics of different angle measurement methods. This leads to limited improvement in multipath resistance and accuracy, poor adaptability, and difficulty in meeting the angle measurement requirements of complex dynamic environments.

[0004] Therefore, there is an urgent need in this field for a radar angle measurement technology solution that can integrate the advantages of multiple angle measurement methods, combine track characteristics for optimization, effectively suppress multipath interference, and improve angle measurement accuracy and track stability. Summary of the Invention

[0005] In view of the above-mentioned shortcomings of the existing technology, the present invention provides an anti-multipath radar angle measurement system and method based on integrated angle measurement, which can effectively overcome the defects of the existing technology, such as difficulty in effectively suppressing multipath interference, low angle measurement accuracy, and poor track start-up stability.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The anti-multipath radar angle measurement system based on integrated angle measurement includes an angle measurement fusion module, a track batching optimization module, a track association optimization module, and a track smoothing processing module; The angle fusion module generates multi-source pitch angle candidate data through sum-difference angle measurement and sum-supplement angle measurement; The track batch optimization module performs batch processing on multi-source pitch angle candidate data of multiple track points during the track batching stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each track point. The track association optimization module calculates the Euclidean distance between the three-dimensional coordinates of the multi-source pitch angle candidate data of each point track and the historical track during the track tracking stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each point track. The track smoothing module smooths the track altitude sequence and outputs a smoothed track altitude sequence to reduce noise interference and improve the stability of altitude estimation.

[0007] Preferably, the angle measurement fusion module includes a sum-difference angle measurement unit and a sum-and-sum angle measurement unit; The sum-difference angle measurement unit adds and subtracts the echo signals received from the upper and lower arrays, calculates the difference and ratio to obtain the target deflection angle, and outputs two candidate elevation angle data using the maximum amplitude method and the centroid method, respectively. , ; When the target is simultaneously covered by multiple elevation beams, the angle measurement unit utilizes the multi-beam signal strength characteristics to output two candidate elevation angle data using the maximum amplitude method and the centroid method, respectively. , ; Among them, the maximum amplitude method selects the angle corresponding to the point with the maximum signal amplitude, while the centroid method calculates the centroid of the angle based on the signal amplitude distribution.

[0008] Preferably, the trajectory batch optimization module performs batch processing on multi-source pitch angle candidate data of multiple points during the trajectory batching stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each point, including: S21. Data Input: For the i-th point, i=1,2,…,M, where M is the number of times the target is reliably detected in the approval rule starting from M / N, collect the corresponding multi-source pitch angle candidate data. , , , And the multi-source pitch angle candidate data of all points are combined into a vector vec: ; S22. Subvector partitioning: Divide the vector vec into three subvectors subVec1, subVec2, and subVec3. Each subvector contains a maximum of 4 elements, ensuring that they do not exceed the bounds. ; ; ; If the length of the vector vec is insufficient, only the usable portion is used; S23. Calculate the global average: ; in, The global average pitch angle, Indicates pitch angle Belongs to vector vec, The length of vector vec; S24. Select the optimal pitch angle: For the j-th subvector subVec j j=1,2,3, Filtering and global average pitch angle The closest optimal pitch angle: ; in, For the j-th subvector subVec j The closest to the global average pitch angle The optimal pitch angle, Indicates pitch angle Belonging to the j-th subvector subVec j ; The subvector that is closest to the global average pitch angle The optimal pitch angles form a candidate vector closeVec; S25. Result Assignment and Coordinate Update: Assign the optimal pitch angle from the candidate vector closeVec to each point in sequence: ; in, Let be the final pitch angle of the i-th point. This represents the (i-1)th element in the candidate vector closeVec; Update the 3D coordinates based on the final pitch angle of each point: ; ; ; Among them, (X) i ,Y i Z i Let R be the updated 3D coordinates of the i-th point. i , denoted as the distance and azimuth of the i-th point, respectively.

[0009] Preferably, during the track tracking phase, the track association optimization module calculates the Euclidean distance between the three-dimensional coordinates corresponding to the multi-source pitch angle candidate data of each point track and the historical track, selects the optimal pitch angle, and updates the three-dimensional coordinates of each point track, including: S31. Coordinate Transformation: For the multi-source pitch angle candidate data of the current point... Given k=1,2,3,4, calculate the corresponding three-dimensional coordinates (X, Y, X) using the polar to rectangular coordinate conversion formula. k ,Y k Z k ): ; ; ; Among them, R, These are the distance and azimuth of the current point, respectively; S32. Calculate Euclidean distance: For the three-dimensional coordinates (X, Y, Z) of the current point... k ,Y k Z k The vertical coordinate Z in ) k Calculate its three-dimensional coordinates (X and Y) relative to the last point of the historical track. last ,Y last Z last The vertical coordinate Z in ) last The Euclidean distance d between them k : ; S33. Select the optimal pitch angle: Sort the four distances d1, d2, d3, and d4, and select the candidate pitch angle data corresponding to the shortest distance as the optimal pitch angle for the current point. And update the three-dimensional coordinates.

[0010] Preferably, the track smoothing module smooths the track altitude sequence and outputs a smoothed track altitude sequence to reduce noise interference and improve altitude estimation stability, including: The track smoothing module smooths the track altitude sequence using a sliding window mean filter, outputting a smoothed track altitude sequence, specifically including: S41, Window settings: Set the window size to 4, containing the current point and its three preceding points; S42. Smoothing Rule: Let the track altitude sequence be {h1, h2, ..., h...} N For the height of the first three points, retain the original values; for the fourth and subsequent points, calculate the average height within the window. ; Among them, h m 'This represents the average altitude within a window containing the m-th point in the track altitude sequence. h n The altitude of the nth point in the track altitude sequence; S43, Height Update: Update the average height h m 'Assign the value to the m-th point in the track altitude sequence to complete the data update; S44, Output the smoothed track altitude sequence.

[0011] The anti-multipath radar angle measurement method based on integrated angle measurement includes the following steps: S1. Generate multi-source pitch angle candidate data through sum-difference angle measurement and sum-supplement angle measurement; S2. During the initial batching stage of the flight path, the multi-source pitch angle candidate data of multiple points are processed in batches, the optimal pitch angle is selected, and the three-dimensional coordinates of each point are updated. S3. During the track tracking phase, calculate the Euclidean distance between the three-dimensional coordinates corresponding to the multi-source pitch angle candidate data of each point and the historical track, select the optimal pitch angle, and update the three-dimensional coordinates of each point. S4. Smooth the track altitude sequence and output the smoothed track altitude sequence to reduce noise interference and improve the stability of altitude estimation.

[0012] Compared with the prior art, the anti-multipath radar angle measurement system and method based on integrated angle measurement provided by the present invention has the following beneficial effects: 1) Significantly enhanced multipath resistance: The high sensitivity of the sum and difference angle measurement and the strong stability of the sum and difference angle measurement, combined with multiple sub-methods such as the maximum amplitude method and the centroid method, form a complementary suppression mechanism, which effectively reduces the impact of multipath interference on the angle measurement results and avoids the "jumping" phenomenon; 2) Improved angle measurement accuracy and robustness: By statistically filtering historical track data, angle jump values ​​are eliminated, and instantaneous errors are corrected by utilizing the continuity of target motion; cross-validation of multiple algorithm results, combined with sliding window mean filtering, further reduces noise interference and improves the accuracy and reliability of angle estimation. 3) Track batching stability optimization: During the track batching stage, multi-source pitch angle candidate data are processed in batches. The optimal pitch angle is selected by guiding the global average value and the distance matching strategy, which effectively suppresses multipath effects and ensures stable track batching in complex scenarios such as long distances. 4) Strong environmental adaptability: It adopts a modular design and adaptive selection mechanism, which can flexibly adapt to the optimal angle measurement algorithm combination according to different multipath intensities, distance ranges and other dynamic environments, so as to meet the angle measurement needs in diverse scenarios. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0014] Figure 1 This is a schematic diagram of the process of the present invention; Figure 2 This is a schematic diagram of the workflow of the trajectory batch optimization module in this invention; Figure 3 This is a schematic diagram of the workflow of the trajectory association optimization module in this invention; Figure 4 This is a schematic diagram of the workflow of the trajectory smoothing module in this invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0016] The following describes the specific functional modules and technical effects of the anti-multipath radar angle measurement system based on integrated angle measurement provided by this invention, using concrete examples. The system functional modules include: an angle measurement fusion module, a track batching optimization module, a track association optimization module, and a track smoothing processing module. The angle fusion module generates multi-source pitch angle candidate data through sum-difference angle measurement and sum-supplement angle measurement; The track batch optimization module performs batch processing on multi-source pitch angle candidate data of multiple track points during the track batching stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each track point. The track association optimization module calculates the Euclidean distance between the three-dimensional coordinates of the multi-source pitch angle candidate data of each point track and the historical track during the track tracking stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each point track. The track smoothing module smooths the track altitude sequence and outputs a smoothed track altitude sequence to reduce noise interference and improve the stability of altitude estimation.

[0017] I. Angle Measurement Fusion Module The angle measurement fusion module includes a sum-difference angle measurement unit and a sum-and-sum angle measurement unit; The sum-difference angle measurement unit adds and subtracts the echo signals received from the upper and lower arrays, calculates the difference and ratio to obtain the target deflection angle, and outputs two candidate elevation angle data using the maximum amplitude method and the centroid method, respectively. , ; When the target is simultaneously covered by multiple elevation beams, the angle measurement unit utilizes the multi-beam signal strength characteristics to output two candidate elevation angle data using the maximum amplitude method and the centroid method, respectively. , ; Among them, the maximum amplitude method selects the angle corresponding to the point with the maximum signal amplitude, while the centroid method calculates the centroid of the angle based on the signal amplitude distribution.

[0018] II. Flight Track Initial Batch Optimization Module In the initial stage of track batching, the track batching optimization module performs batch processing on multi-source pitch angle candidate data for multiple tracks, selects the optimal pitch angle, and updates the three-dimensional coordinates of each track. Figure 2 As shown, it includes: S21. Data Input: For the i-th point, i=1,2,…,M, where M is the number of times the target is reliably detected in the approval rule starting from M / N, collect the corresponding multi-source pitch angle candidate data. , , , And the multi-source pitch angle candidate data of all points are combined into a vector vec: ; S22. Subvector partitioning: Divide the vector vec into three subvectors subVec1, subVec2, and subVec3. Each subvector contains a maximum of 4 elements, ensuring that they do not exceed the bounds. ; ; ; If the length of the vector vec is insufficient, only the usable portion is used; S23. Calculate the global average: ; in, The global average pitch angle, Indicates pitch angle Belongs to vector vec, The length of vector vec; S24. Select the optimal pitch angle: For the j-th subvector subVec j j=1,2,3, Filtering and global average pitch angle The closest optimal pitch angle: ; in, For the j-th subvector subVec j The closest to the global average pitch angle The optimal pitch angle, Indicates pitch angle Belonging to the j-th subvector subVec j ; The subvector that is closest to the global average pitch angle The optimal pitch angles form a candidate vector closeVec; S25. Result Assignment and Coordinate Update: Assign the optimal pitch angle from the candidate vector closeVec to each point in sequence: ; in, Let be the final pitch angle of the i-th point. This represents the (i-1)th element in the candidate vector closeVec; Update the 3D coordinates based on the final pitch angle of each point: ; ; ; Among them, (X) i ,Y i Z i Let R be the updated 3D coordinates of the i-th point. i , denoted as the distance and azimuth of the i-th point, respectively.

[0019] III. Track Association Optimization Module During the track tracking phase, the track association optimization module calculates the Euclidean distance between the 3D coordinates of each point's multi-source pitch angle candidate data and the historical track, selects the optimal pitch angle, and updates the 3D coordinates of each point. Figure 3 As shown, it includes: S31. Coordinate Transformation: For the multi-source pitch angle candidate data of the current point... Given k=1,2,3,4, calculate the corresponding three-dimensional coordinates (X, Y, X) using the polar to rectangular coordinate conversion formula. k ,Y k Z k ): ; ; ; Among them, R, These are the distance and azimuth of the current point, respectively; S32. Calculate Euclidean distance: For the three-dimensional coordinates (X, Y, Z) of the current point... k ,Y k Z k The vertical coordinate Z in ) k Calculate its three-dimensional coordinates (X and Y) relative to the last point of the historical track. last ,Y last Z last The vertical coordinate Z in ) last The Euclidean distance d between them k : ; S33. Select the optimal pitch angle: Sort the four distances d1, d2, d3, and d4, and select the candidate pitch angle data corresponding to the shortest distance as the optimal pitch angle for the current point. And update the three-dimensional coordinates.

[0020] IV. Track Smoothing Module The track smoothing module smooths the track altitude sequence and outputs a smoothed track altitude sequence to reduce noise interference and improve the stability of altitude estimation. Figure 4 As shown, it includes: The track smoothing module smooths the track altitude sequence using a sliding window mean filter, outputting a smoothed track altitude sequence, specifically including: S41, Window settings: Set the window size to 4, containing the current point and its three preceding points; S42. Smoothing Rule: Let the track altitude sequence be {h1, h2, ..., h...} N For the height of the first three points, retain the original values; for the fourth and subsequent points, calculate the average height within the window. ; Among them, h m 'This represents the average altitude within a window containing the m-th point in the track altitude sequence. h n The altitude of the nth point in the track altitude sequence; S43, Height Update: Update the average height h m 'Assign the value to the m-th point in the track altitude sequence to complete the data update; S44, Output the smoothed track altitude sequence.

[0021] Based on the aforementioned anti-multipath radar angle measurement system based on integrated angle measurement, this invention also discloses an anti-multipath radar angle measurement method based on integrated angle measurement, such as... Figure 1 As shown, it includes the following steps: S1. Generate multi-source pitch angle candidate data through sum-difference angle measurement and sum-supplement angle measurement; S2. During the initial batching stage of the flight path, the multi-source pitch angle candidate data of multiple points are processed in batches, the optimal pitch angle is selected, and the three-dimensional coordinates of each point are updated. S3. During the track tracking phase, calculate the Euclidean distance between the three-dimensional coordinates corresponding to the multi-source pitch angle candidate data of each point and the historical track, select the optimal pitch angle, and update the three-dimensional coordinates of each point. S4. Smooth the track altitude sequence and output the smoothed track altitude sequence to reduce noise interference and improve the stability of altitude estimation.

[0022] To better illustrate the advantages of the technical solution of this application, the following comparative experiments will be used for verification.

[0023] This comparative experiment verified multiple sets of angle measurement data under different scenarios, frequencies, heights, distances, and attitudes. Through comparative analysis, the improvement effect of this invention on angle measurement accuracy was verified, as shown in Table 1: Table 1 Comparison of Angle Measurement Accuracy

[0024] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An anti-multipath radar angle measurement system based on integrated angle measurement, characterized in that: It includes an angle fusion module, a track batching optimization module, a track association optimization module, and a track smoothing processing module; The angle fusion module generates multi-source pitch angle candidate data through sum-difference angle measurement and sum-supplement angle measurement; The track batch optimization module performs batch processing on multi-source pitch angle candidate data of multiple track points during the track batching stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each track point. The track association optimization module calculates the Euclidean distance between the three-dimensional coordinates of the multi-source pitch angle candidate data of each point track and the historical track during the track tracking stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each point track. The track smoothing module smooths the track altitude sequence and outputs a smoothed track altitude sequence to reduce noise interference and improve the stability of altitude estimation.

2. The anti-multipath radar angle measurement system based on integrated angle measurement according to claim 1, characterized in that: The angle measurement fusion module includes a sum-difference angle measurement unit and a sum-and-sum angle measurement unit; The sum-difference angle measurement unit adds and subtracts the echo signals received from the upper and lower arrays, calculates the difference and ratio to obtain the target deflection angle, and outputs two candidate elevation angle data using the maximum amplitude method and the centroid method, respectively. , ; When the target is simultaneously covered by multiple elevation beams, the angle measurement unit utilizes the multi-beam signal strength characteristics to output two candidate elevation angle data using the maximum amplitude method and the centroid method, respectively. , ; Among them, the maximum amplitude method selects the angle corresponding to the point with the maximum signal amplitude, while the centroid method calculates the centroid of the angle based on the signal amplitude distribution.

3. The anti-multipath radar angle measurement system based on integrated angle measurement according to claim 2, characterized in that: The trajectory batch optimization module performs batch processing on multi-source pitch angle candidate data for multiple points during the trajectory batching stage, selects the optimal pitch angle, and updates the three-dimensional coordinates of each point, including: S21. Data Input: For the i-th point, i=1,2,…,M, where M is the number of times the target is reliably detected in the approval rule starting from M / N, collect the corresponding multi-source pitch angle candidate data. , , , And the multi-source pitch angle candidate data of all points are combined into a vector vec: ； S22. Subvector partitioning: Divide the vector vec into three subvectors subVec1, subVec2, and subVec3. Each subvector contains a maximum of 4 elements, ensuring that they do not exceed the bounds. ； ； ； If the length of the vector vec is insufficient, only the usable portion is used; S23. Calculate the global average: ； in, The global average pitch angle, Indicates pitch angle Belongs to vector vec, The length of vector vec; S24. Select the optimal pitch angle: For the j-th subvector subVec j j=1,2,3, Filtering and global average pitch angle The closest optimal pitch angle: ； in, For the j-th subvector subVec j The closest to the global average pitch angle The optimal pitch angle, Indicates pitch angle Belonging to the j-th subvector subVec j ; The subvector that is closest to the global average pitch angle The optimal pitch angles form a candidate vector closeVec; S25. Result Assignment and Coordinate Update: Assign the optimal pitch angle from the candidate vector closeVec to each point in sequence: ； in, Let be the final pitch angle of the i-th point. This represents the (i-1)th element in the candidate vector closeVec; Update the 3D coordinates based on the final pitch angle of each point: ； ； ； Among them, (X) i ,Y i Z i Let R be the updated 3D coordinates of the i-th point. i , denoted as the distance and azimuth of the i-th point, respectively.

4. The anti-multipath radar angle measurement system based on integrated angle measurement according to claim 3, characterized in that: During the track tracking phase, the track association optimization module calculates the Euclidean distance between the three-dimensional coordinates corresponding to the multi-source pitch angle candidate data of each point and the historical track, selects the optimal pitch angle, and updates the three-dimensional coordinates of each point, including: S31. Coordinate Transformation: For the multi-source pitch angle candidate data of the current point... Given k=1,2,3,4, calculate the corresponding three-dimensional coordinates (X, Y, X) using the polar to rectangular coordinate conversion formula. k ,Y k Z k ): ； ； ； Among them, R, These are the distance and azimuth of the current point, respectively; S32. Calculate Euclidean distance: For the three-dimensional coordinates (X, Y, Z) of the current point... k ,Y k Z k The vertical coordinate Z in ) k Calculate its three-dimensional coordinates (X and Y) relative to the last point of the historical track. last ,Y last Z last The vertical coordinate Z in ) last The Euclidean distance d between them k : ； S33. Select the optimal pitch angle: Sort the four distances d1, d2, d3, and d4, and select the candidate pitch angle data corresponding to the shortest distance as the optimal pitch angle for the current point. And update the three-dimensional coordinates.

5. The anti-multipath radar angle measurement system based on integrated angle measurement according to claim 4, characterized in that: The track smoothing module smooths the track altitude sequence and outputs a smoothed track altitude sequence to reduce noise interference and improve altitude estimation stability, including: The track smoothing module smooths the track altitude sequence using a sliding window mean filter, outputting a smoothed track altitude sequence, specifically including: S41, Window settings: Set the window size to 4, containing the current point and its three preceding points; S42. Smoothing Rule: Let the track altitude sequence be {h1, h2, ..., h...} N For the height of the first three points, retain the original values; for the fourth and subsequent points, calculate the average height within the window. ； Among them, h m 'This represents the average altitude within a window containing the m-th point in the track altitude sequence. h n The altitude of the nth point in the track altitude sequence; S43, Height Update: Update the average height h m 'Assign the value to the m-th point in the track altitude sequence to complete the data update; S44, Output the smoothed track altitude sequence.

6. A multipath radar angle measurement method based on integrated angle measurement, applied to the multipath radar angle measurement system based on integrated angle measurement as described in claim 1, characterized in that: Includes the following steps: S1. Generate multi-source pitch angle candidate data through sum-difference angle measurement and sum-supplement angle measurement; S2. During the initial batching stage of the flight path, the multi-source pitch angle candidate data of multiple points are processed in batches, the optimal pitch angle is selected, and the three-dimensional coordinates of each point are updated. S3. During the track tracking phase, calculate the Euclidean distance between the three-dimensional coordinates corresponding to the multi-source pitch angle candidate data of each point and the historical track, select the optimal pitch angle, and update the three-dimensional coordinates of each point. S4. Smooth the track altitude sequence and output the smoothed track altitude sequence to reduce noise interference and improve the stability of altitude estimation.

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