Multiresolutional Quasi-Monte Carlo-based particle filters

摘要：

Quasi-Monte Carlo (QMC)-based particle filters can obtain more accurate estimation than the general particle filters, with formidable computational complexity, however. Spatial-domain multiresolutional particle filters are more efficient by reducing the number of particles, but unevenly samples may cause estimation error. Aiming at these, we combine QMC numerical technique and multiresolutional methodology to improve the accuracy of filtering and computational efficiency. According to the idea, two QMC-based particle filters using thresholded wavelets in the spatial domain are proposed in this paper. The simulation shows that both the algorithms reduce the number of particles, meanwhile maintaining the estimation performance of particle filters with QMC methodology.

关键词： Particle filters QMC Computational efficiency Wavelets Multiresolutional techniques

作者: LINGLING ZHAO PEIJUN MA XIAOHONG SU

作者单位: School of Computer Science and Technology Harbin Institute of Technology Harbin,Heilongjiang,CHINA

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 2248-2252

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）