|Source||CMES: Computer Modeling in Engineering & Sciences, Vol. 106, No. 6, pp. 379-393, 2015|
|Download||Full length paper in PDF format. Size = 3,314,070 bytes|
|Keywords||dynamic, particle filter, integrated navigation, hybrid adaptive|
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.