A Multiple Shape-Target Tracking Algorithm by Using MCMC Sampling

Traditional multiple target tracking (MTT) algorithms such as JPDA, MHT, a basic assume that the targets are points source. This is unrealistic in many cases. We consider targets with certain geometrical shape and they may give multiple measurements using the Markov Chain Monte Carlo (MCMC) approach. We aim at estimating the states of targets, their shape parameters, and number of targets. The proposed approach is based on the clustering process of finite mixture models (FMM), where the parameters of the FMM are obtained by the MCMC sampler. The states of the targets are estimated by equivalent measurement (EQM). The final experiment of three target tracking verifies the proposed algorithm.

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