Abstract
In order to improve the performance of particle data association filter algorithm for multi-target tracking, an improved multi-target tracking algorithm is proposed in this paper. Particle swarm optimization (PSO) technology is introduced in the particle filter (PF) algorithm and a new best fitness function of particles is defined to better approximate the true posterior distribution, fuzzy clustering technique is combined for data association in the proposed algorithm. Simulation results show that the proposed algorithm has better performance than the conventional particle data association filter algorithm for passive multi-target tracking.
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