Multi-target particle filter tracking-before-detection method based on target re-tracking

Abstract

The invention discloses a multi-target particle filter tracking-before-detection method based on target re-tracking, and the method comprises the steps that: the sorting of a tracking particle swarm is carried out according to the particle weight value of a target which is tracked and has a pb greater than a given threshold value in a tracking link, and the state mean value of the first N / 50 particles is calculated; new particles are generated by taking the state mean value as a central point, the state information of the last 0.98*N particles of the tracking particle swarm is replaced, the existing values of the particle swarm are all set to be 1, high-quality particles are reserved, the particle swarm is updated, the utilization rate of the particles is improved, tracking traces are enabled to be close to a real target more quickly, and the tracking precision of the target is improved. Besides, false trace points are enabled to be closer to the real target more quickly, and the falsealarm rate and the tracking error of the target are reduced by calculating the distance between the target and the first track point when the length leni of the tracking track of the target is 3 anddeleting the false track if the distance is too large and the initial state information of the target is inaccurate.

Description

technical field [0001] The invention belongs to the technical field of radar tracking before detection, relates to the technical field of multi-radar multi-target particle filter tracking before detection, and in particular relates to a multi-target particle filter tracking-before-detection method based on target re-tracking Background technique [0002] The multi-radar multi-target particle filter tracking before detection algorithm is a method of using multi-radar to detect and track multiple weak targets. It often adopts a two-layer particle filter structure, that is, the target tracking layer and the target detection layer. The target detection layer is responsible for detecting and discovering new targets, and the target tracking layer is responsible for tracking and estimating each target that has been discovered so far, and each target has a separate tracking particle swarm. [0003] When tracking and filtering the discovered targets at the target tracking layer, the ...

AI Technical Summary

Problems solved by technology

[0003] When tracking and filtering the discovered targets at the target tracking layer, the newly discovered targets usually have low tracking accuracy and are far away from the real track of the target. When the real track of the target is relatively close, due to the large tracking threshold of the target tracking layer, the tracking particle swarm of the newly discovered target is easy to deviate from the original target track, gradually approaching another target track, or even close to another target track. Merge, and eventually lead to the problem of missed detection of the target

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