Particle Swarm Optimization in Geomagnetic Matching Navigation

Abstract

In order to increase the localization accuracy of traditional geomagnetic matching algorithms, this paper propose a new geomagnetic matching algorithm based on improved Particle swarm optimization. Traditional PSO algorithm has premature convergence of particles, which not only destroys the diversity of particles, but also leads to mismatches. In this paper, the modified Metropolis criterion is applied to particle swarm optimization (PSO), and the campaign idea is introduced into the campaign algorithm, so as to obtain an improved particle swarm optimization geomagnetic matching algorithm. Finally, through simulation analysis, the matching accuracy and matching time based on improved PSO and traditional PSO matching algorithm are compared. The simulation results show that the improved PSO algorithm outperforms the traditional PSO algorithm, and the matching time is slightly longer than that of PSO algorithm, but meets the real-time requirement.