Interacting MCMC particle filter for tracking maneuvering target
In this paper, a new method, named interacting MCMC particle filter, is proposed to track maneuvering target. The particles are sampled from the target posterior distribution via direct interacting MCMC sampling method, which avoids sample impoverishment and increases the robustness of the algorithm. Moreover, the interacting MCMC particle filter algorithm accelerates the MCMC convergence rate via propagating each particle based on both its history information and the information from other particles.
particle filter markov chain monte carlo particle swarm maneuvering target tracking