A Detection and Tracking Method of Radar Weak Target Using Particle Filter

Abstract

The invention belongs to the technical field of communication electronics, and relates to a radar faint target detection and tracking method based on particle filter. The method provided by the invention comprises the steps that the number of particles of traditional particle filter is reduced; a small number of sampling points are sampled from the possible distributions of a tracked target; different weights are given to the sampling points; and sequential smoothing is carried out on transformed sampling points to finally output the acquired estimation of the target location. The simulation results show that the algorithm provided by the invention has higher positioning accuracy than the existing particle filter algorithm and has lower computational cost. The provided algorithm carries out a total of 100 times of Monte Carlo simulation detection with the signal-to-noise ratio of 0 dB to15 dB. The detection probability is high. The detection probability of the improved algorithm is significantly better than the detection probability of the existing particle filter algorithm at 7 dB, and the computational cost is less than the computational cost of the existing particle filter algorithm.

Description

Technical field [0001] The invention belongs to the technical field of communication electronics, and relates to a radar weak target detection and tracking method using particle filtering. Background technique [0002] In order to cope with the challenges that non-cooperative targets such as stealth targets bring to modern radars, passive location and tracking methods are booming. A key issue in passive system signal detection technology is to detect and track weak mobile targets. Weak target refers to a low detectable target with a small radar reflection cross-sectional area, resulting in weak reflection echo. When these targets are illuminated by electromagnetic waves, the intensity of the backscattered waves decreases significantly, and the echo signal is very weak. At the same time, these typical weak targets often have very high mobility, that is, these targets can change their original motion rules, resulting in a degree of change in the motion model that exceeds the range...

AI Technical Summary

Problems solved by technology

[0012] (1) The calculation cost is huge, and it is easy to cause data processing unit overflow

[0013] (2) The sampling process is single-judged, causing particle degradation and loss of estimation accuracy

At the same time, in order to solve the problem of particle degradation after resampling, the number of particles needs to be increased, which further increases the calculation cost

[0014] (3) It is easy to generate jump points of measurement data, resulting in angular ambiguity and model mismatch

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