A novel multi-sensor multiple model particle filter

摘要：

The large amount of calculation always severely restricts the application domain expansion of particle filter, a novel multi-sensor multiple model particle filtering algorithm based on particle weight optimization is proposed. In the multiple model particle filter framework, the optimization method of particle weight is realized by the extraction and utilization of redundancy and complementary information from latest multi-sensor observations. Due to weaken the adverse influence of random observations noise, the stability and reliability is effective improved. The theoretical analysis and experimental results show that the new algorithm can improve the filter precision but also lessens computational burden in nonlinear system estimation with multi-sensor multiple model characteristic.

关键词： Multiple Model Particle Filter Particle Weight Optimization Weighting Fusion Interacting Multiple Model

作者: HU Zhen-tao LIU Xian-xing LI Jie

作者单位: Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng, 47500, P.R.China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 1718-1722

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）