Improving the Gaussian Sum Particle filtering by MMSE constraint

摘要：

In the paper,we proposed a new modification to the Gaussian Sum Particle filtering (GSPF) by incorporating a Minimum Mean Square Error constraint (MMSE-GSPF) in tracking parameter variation of Dynamic State Space model,the algorithm complexity is reduced yet.In addition,the MMSE-GSPF also shows better performance in tracking of time-varying parameters than the original Gaussian Sum Particle filtering.

关键词： Dynamic State Space model MMSE-GSPF Gaussian Sum Particle filtering Gaussian Sum filtering

作者: Chao Shao

作者单位: Xian Institute of post and telecommunications,710061

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）