Novel particle filter algorithm based on adaptive particle swarm optimization and its application to radar target tracking

A particle filter algorithm based on dynamic neighborhood adaptive particle swarm optimization(DPSO-PF) is presented in order to solve the problem of the low precision and complicated calculation of particle filter based on particle swarm optimization(PSO-PF) algorithm.This algorithm can dynamically adjust the particle neighborhood environment,where each particle can adjust the number of particles in the neighborhood based on self-adaptation basis according to the neighborhood environment and their own position information,accordingly a best balance is achieved between optimal seeking and convergence rate.Finally,different models are used for simulation experiment and the results show that the proposed algorithm improves the real-time performance and the precision of maneuvering target tracking by using radar.