Dynamic Population Adaptive Particle Swarm Optimized Particle Filter for Integrated Navigation

Particle filter based on particle swarm optimization algorithm (PSO-PF) is not precise and trapping in local optimum easily, it is not able to satisfy the requirement of advanced integrated navigation system. In order to solve these problems, a novel particle filter algorithm based on dynamic neighborhood population adaptive particle swarm optimization (DPSO-PF) is presented in this paper. This new particle filter can dynamically adjust the particle neighborhood environment, wherein 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 indicate that this new algorithm improves the precision of GPS/INS integrated navigation system. Key-Words: dynamic, particle filter, integrated navigation, neighborhood, population