CN-121978643-A - Data fusion processing method, device, equipment and medium

CN121978643ACN 121978643 ACN121978643 ACN 121978643ACN-121978643-A

Abstract

The invention relates to a data fusion processing method, a device, equipment and a medium, which are based on land-based Ku wave band tetrahedral array low-altitude monitoring radar, and comprise the steps of measuring targets by adopting land-based Ku wave band tetrahedral array low-altitude monitoring radar to form a point trace; performing association processing on adjacent point tracks to form temporary tracks; if the temporary track or the stable track is not searched continuously for the relevant point track within the specified times, the temporary track or the stable track is eliminated, and the radar of the invention can effectively improve the angle measurement precision by carrying out fusion processing on the data measured by each area array, thereby improving the tracking capability of the target.

Inventors

LI PENGJU
ZHANG LE
PAN BAICHEN
DUAN XIAOFENG
ZHAO JIA
MA XIAOYA

Assignees

航天时代飞鸿技术有限公司

Dates

Publication Date: 20260505
Application Date: 20251212

Claims (10)

1. A data fusion processing method is characterized in that, the method is based on land-based Ku wave band tetrahedral array low-altitude monitoring radar, and comprises the following steps: S1, measuring a target by adopting a land-based Ku wave band tetrahedral array low-altitude monitoring radar to form a point trace; S2, performing association processing on adjacent point tracks to form temporary tracks; s3, performing association processing on the temporary track and the current track to obtain a stable track, wherein the current track is the next track continuously adjacent to the two adjacent tracks; S4, if the temporary track or the stable track is not searched continuously for the relevant point track within the specified times, the temporary track or the stable track is eliminated.
2. The method of claim 1, wherein the trace comprises four parameters of a distance, altitude, azimuth, and speed of the measurement target, or five parameters of a distance, altitude, azimuth, speed, and RCS value of the measurement target.
3. The method according to claim 1, wherein S2 comprises: S21, when the 1 st track and the 2 nd track of the adjacent tracks are all four parameters, performing association processing according to a four-parameter threshold to generate a four-parameter temporary track, or S22, if one of the 1 st or2 nd tracks of the adjacent tracks is five-parameter, the RCS value of the five-parameter track is assigned to the four-parameter track to generate a five-parameter temporary track, or S23, when the 1 st track and the 2 nd track of the adjacent tracks are five parameters, performing association processing according to a five-parameter threshold to generate a five-parameter temporary track.
4. The method according to claim 1, wherein S3 comprises: S31, when the temporary track is a four-parameter track and the current track is a five-parameter track, performing association processing according to a four-parameter threshold, setting an RCS predicted value of the temporary track as an RCS value of the current track, and generating a five-parameter stable track; s32, when the temporary track is a five-parameter track and the current track is a four-parameter track, performing association processing according to a four-parameter threshold, assigning the RCS predicted value of the five-parameter track to the current track, and taking the temporary track as a five-parameter stable track.
5. The method of claim 4, wherein S3 further comprises S33, when the temporary track is a four-parameter track and the current track is a four-parameter track, performing association processing according to a four-parameter threshold, and taking the four-parameter track as a stable track; 34. when the temporary track is a five-parameter track and the current point track is a five-parameter track, performing association processing according to a five-parameter threshold, and taking the five-parameter track as a stable track.
6. The method of claim 1, wherein S3 further comprises performing track filtering with a Kalman filter after successful trace-pointing and stable track interconnection, and performing track prediction before successful trace-pointing and track interconnection next time.
7. The method according to claim 1, wherein S4 comprises the step of, if the temporary track is not searched for the relevant track 3 or more times in succession, then the temporary track is eliminated; if the stable track is continuous for 5 times or more and no relevant point track is searched, the stable track is eliminated.
8. A data fusion processing device, characterized in that the device is configured to implement the method of any one of claims 1-7, comprising the following modules: the point trace forming module is used for measuring a target by adopting a land-based Ku wave band tetrahedral array low-altitude monitoring radar to form a point trace; the first association processing module is used for carrying out association processing on the adjacent tracks to form temporary tracks; the second association processing module is used for carrying out association processing on the temporary track and the current point track to obtain a stable track, wherein the current point track is the next point track continuously adjacent to the two adjacent point tracks; And the judging module is used for eliminating the temporary track or the stable track if the temporary track or the stable track is not searched continuously for the relevant point track within the specified times.
9. A computer storage medium, characterized in that the medium has stored thereon a computer program which is executed by a processor to implement the method of any of claims 1-7.
10. An electronic device, the electronic device comprising: A memory storing executable instructions; A processor executing the executable instructions in the memory to implement the method of any of claims 1-7.

Description

Data fusion processing method, device, equipment and medium Technical Field The invention belongs to the field of radar data processing, and particularly relates to a data fusion processing method, device, equipment and medium. Background With the rapid development of the unmanned aerial vehicle technology, related events such as illegal reconnaissance, black flight and the like frequently occur, the threat to the public safety of society is increased increasingly, and the radar is an important means for detecting the unmanned aerial vehicle and has important significance in the aspect of defending the unmanned aerial vehicle threat. The unmanned aerial vehicle detection radar generally adopts a mode of scanning by an azimuth dimension machine and scanning by a pitching dimension to search for targets, and because the data rate of the radar is limited in the machine scanning mode, the unmanned aerial vehicle target with high maneuver is difficult to effectively detect and track, and therefore, the data rate of the radar is improved by adopting the mode of scanning by the azimuth dimension and the pitching dimension. In order to solve the problem that a single-sided array radar detection airspace is limited, a four-sided array radar structure is adopted to realize 360-degree full coverage of an azimuth dimension, and meanwhile, a data fusion processing method is needed to further improve the detection effect of the unmanned aerial vehicle. Disclosure of Invention The invention aims to solve the existing problems, and provides a data fusion processing method, a device, equipment and a medium, which are used for solving the problems in the prior art. The data fusion processing method is based on land-based Ku-band tetrahedral array low-altitude surveillance radar and comprises the following steps: S1, measuring a target by adopting a land-based Ku wave band tetrahedral array low-altitude monitoring radar to form a point trace; S2, performing association processing on adjacent point tracks to form temporary tracks; s3, performing association processing on the temporary track and the current track to obtain a stable track, wherein the current track is the next track continuously adjacent to the two adjacent tracks; S4, if the temporary track or the stable track is not searched continuously for the relevant point track within the specified times, the temporary track or the stable track is eliminated. Aspects and any possible implementation as described above, further providing an implementation, where the trace of points includes four parameters of a distance, an altitude, an azimuth, and a speed of the measurement target, or includes five parameters of a distance, an altitude, an azimuth, a speed, and an RCS value of the measurement target. In the aspect and any possible implementation manner as described above, there is further provided an implementation manner, where the S2 includes: S21, when the 1 st track and the 2 nd track of the adjacent tracks are all four parameters, performing association processing according to a four-parameter threshold to generate a four-parameter temporary track, or S22, if one of the 1 st or2 nd tracks of the adjacent tracks is five-parameter, the RCS value of the five-parameter track is assigned to the four-parameter track to generate a five-parameter temporary track, or S23, when the 1 st track and the 2 nd track of the adjacent tracks are five parameters, performing association processing according to a five-parameter threshold to generate a five-parameter temporary track. S31, when the temporary track is a four-parameter track and the current track is a five-parameter track, performing association processing according to a four-parameter threshold, setting an RCS predicted value of the temporary track as an RCS value of the current track, and generating a five-parameter stable track; s32, when the temporary track is a five-parameter track and the current track is a four-parameter track, performing association processing according to a four-parameter threshold, assigning the RCS predicted value of the five-parameter track to the current track, and taking the temporary track as a five-parameter stable track. S33, when the temporary track is a four-parameter track and the current track is a four-parameter track, performing association processing according to a four-parameter threshold, and taking the four-parameter track as a stable track; 34. when the temporary track is a five-parameter track and the current point track is a five-parameter track, performing association processing according to a five-parameter threshold, and taking the five-parameter track as a stable track. In the aspect and any possible implementation manner described above, there is further provided an implementation manner, and S3 further includes performing track filtering with a kalman filter after successful track pointing and stable track interconnection, and performing track prediction before successful