Hybrid Adaptive Particle Swarm Optimized Particle Filter for Integrated Navigation System
Zhimin Chen, Yuanxin Qu, Tongshuang Zhang, Xiaoshu Bai, Xiaohong Tao and Yong Liu

doi:10.3970/cmes.2015.106.379
Source CMES: Computer Modeling in Engineering & Sciences, Vol. 106, No. 6, pp. 379-393, 2015
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Keywords dynamic, particle filter, integrated navigation, hybrid adaptive
Abstract

Particle swarm optimization algorithm based particle filter is trapping in local optimum easily, it is not able to satisfy the requirement of modern integrated navigation system. In order to solve the problem, A novel particle filter algorithm based on hybrid adaptive particle swarm optimization(HPSO-PF) is presented in this paper. This improved particle filter will conduce to finding the ideal solution domain by making use of the global convergence of artificial fish swarm and enhancement of fusion precision by guiding particles to move toward the high likelihood area through particle swarm optimization. Finally different models are used for simulation and the experiment results show that this new particle filter improves the precision of integrated navigation system.

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