WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 11, 2015
Dynamic Population Adaptive Particle Swarm Optimized Particle Filter for Integrated Navigation
Authors: Zhimin Chen, Yuming Bo, Yuanxin Qu, Xiaodong Ling, Xiaohong Tao, Yong Liu
Abstract: 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.
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Keywords: dynamic, particle filter, integrated navigation, neighborhood, population
Pages: 235-244
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #28