Particle Filter-Based Track-before-Detective for Weak Target
基于粒子滤波的弱目标检测前跟踪算法

In this paper, a multiple model particle filter algorithm is presented for the moving weak target in the low SNR environment. Because of the particle's degeneracy, the detection probability and tracking accuracy of the particle filter based track-before-detective will descend in the case of the signal of the target gets weaker, the target is maneuvering or the signal amplitude fluctuation is strong. With this improved algorithm based on the particle filter, add the new particles before each cycle, and the distribution of new particles is determined by the average method and the estimation results of latest moment. Theoretical result and numerical compulation of the partical filter-based TBD algorithm is given in this paper. The simulation experiment illustrates the improved particle filter-based TBD algorithm can detect the weak target with a low SNR.