A comparison of nonlinear filtering approaches for Radar target-tracking performances

Nonlinear problem of maneuvering target is a hot and difficult topic in radar target tracking fielding. In this paper, we firstly introduces several mainstream non-linear filtering methods in tracking fielding, then, pay more attention to analyses the uncertainty sampling method, random sampling method and Markov chain Monte Carlo algorithms, and with its improving methods by introducing reversible jump ratio. we present a comprehensive picture to see the performance by comparing among classical tracking methods combining with RJMCMC method, which include the PF, EKF-PF, UKF-PF techniques from other literature that have seen wide application in Radar target tracking field. Simulations on maneuvering target radar tracking are carried out to validate the performance of the proposed scheme.