Low and slow small target tracking method based on polar coordinate system

Abstract

The invention relates to a low and slow small target tracking method based on a polar coordinate system. The technical feature is that the method comprises the following steps: step 1. establishing atemporary track by using measurement points scanned by a radar for the first time as track heads respectively; step 2. after the radar scans the measurement point for the second time, determining a relevant wave gate by using speed limit; step 3. after the radar scans the measurement point for the third time, for the temporary track with a trace point number of 2, determining the relevant wave gate through Kalman filtering of the polar coordinate system; step 4. moving the track with a trace point number of 3 in a temporary track set into a reliable track set; step 5. after the radar scans a new measurement point, firstly performing association updating with the reliable track set, and if non-associated measurement points still exist, performing association updating with the temporary track set; and step 6. traversing all tracks, if a certain track is not updated exceeding a certain time, performing track is extinction or extrapolation. By adoption of the low and slow small target tracking method provided by the invention, a decoupling problem and a conversion error are avoided, and meanwhile the calculated amount is reduced.

Description

technical field [0001] The invention belongs to the technical field of radar, and relates to a low-slow and small-target tracking method, in particular to a low-slow and small-target tracking method based on a polar coordinate system. Background technique [0002] The detection and tracking of low, slow and small targets has always been a research hotspot and difficulty in the field of radar technology. Low-slow and small targets (low-altitude and slow-speed small targets) refer to targets with small RCS, slow flight speed, suitable for low-altitude flight, and more flexible and maneuverable implementation of low-altitude and ultra-low-altitude penetration. The radar reflection area of ​​low, slow and small targets is very small, resulting in small and weak target echoes; coupled with its slow flight speed, the Doppler effect caused by it is not obvious, making it difficult for radar to effectively detect targets in the frequency domain; In addition, the flying altitude of ...

AI Technical Summary

Problems solved by technology

The radar reflection area of ​​low, slow and small targets is very small, resulting in small and weak target echoes; coupled with its slow flight speed, the Doppler effect caused by it is not obvious, making it difficult for radar to effectively detect targets in the frequency domain; In addition, the flying altitude of low, slow and small targets is low, and the surrounding environment is relatively complex, and the target signal is often easily covered by ground clutter and interference signals.

To sum up, low-slow and small targets have the problems of weak echo, strong clutter influence, and Doppler frequency close to clutter, which makes it very difficult for radar to detect and track them

[0003] In order to solve the problem of radar detection and tracking of low, slow and small targets, some studies consider balloon-borne radar or overhead looking down radar. Compared with ground radar, this type of air-to-ground radar can overcome the influence of earth curvature, topography and complex background environment , but the air-to-ground look-down radar has strong ground clutter reflection echoes in most areas of its range of action, so it must rely on advanced signal processing technology to effectively suppress the clutter. In addition, its complexity is relatively high. The cost of engineering implementation is too high; in terms of radar data processing technology, Track Before Detection (TBD) technology can realize signal detection and tracking under low SNR, it does not make threshold judgment on the echo data received by radar, but It directly uses the original observation data for tracking and filtering processing, estimates the target state information, and then performs threshold judgment after processing, so it can improve the detection and tracking ability of low-slow and small targets. Although this algorithm can reduce the probability of missed detection, it is not effective. It is difficult to eliminate false alarm points, and the amount of calculation is large, which is difficult to realize in engineering; in the tracking of low, slow and small targets, conventional radar only uses position information such as radial distance, azimuth angle, and elevation angle. Puller information is also used in target tracking problems, such as using the radial velocity limit to eliminate clutter false alarm points, but in the tracking and filtering problems in the Cartesian coordinate system, if the state vector increases the radial velocity dimensional information, The linearity of the state equation cannot be maintained, and the computational complexity of tracking and filtering will be increased, so the estimated range of radial velocity can only be used to filter out the target track, which has poor robustness

Images