Particle Filter Based on Chaos Particle Swarm Optimization

摘要：

　　Particle Filter based on Particle Swarm Optimization algorithm (PSO-PF) is not only imprecise enough but also easy to get into local optimum.In order to solve the problems above, a new algorithm named CPSO-PF is proposed.This algorithm introduces chaos theory to initialize particle, which leads the particle distribution more uniform and which ensures the initial particle diversified, It reinitializes disadvantage particles, updates global optimal particle with the thought of chaos mutation and updates inert partides with backward motion method so as to improve the prediction precision of algorithm, to increase the diversity of particles and to avoid the local optimum.The experimental results show that this algorithm compared with PSO-PF, enhances the precision prediction of calculation and improves the real-time performance of the algorithm.

关键词： Particle Filter Chaos Particle Swarm Optimization Mutation

作者: Rui LI Chang-Xu LIU Fu-Zhong NIAN

作者单位: School of Computer and Communication Lanzhou University of Technology,Lanzhou,China

会议类型: 国内会议

会议名称: 第四届信息电子与计算机工程国际会议(The 4th International Conference on Information ,Electronic and Computer Science)

会议地点: 泰安

会议语种:英文

页码: 195-198

在线出版日期: 2012-11-24（万方平台首次上网日期，不代表论文的发表时间）