Quasi-Monte Carlo Gaussian Particle Filtering Acceleration Using CUDA

摘要：

A CUDA accelerated Quasi-Monte Carlo Gaussian particle filter (QMC-GPF) is proposed to deal with real-time non-linear non-Gaussian problems. GPF is especially suitable for parallel implementation as a result of the elimination of resampling step. QMC-GPF is an efficient counterpart of GPF using QMC sampling method instead of MC. Since particles generated by QMC method provides the best-possible distribution in the sampling space, QMC-GPF can make more accurate estimation with the same number of particles compared with traditional particle filter. Experimental results show that our GPU implementation of QMC-GPF can achieve the maximum speedup ratio of 95 on NVIDIA GeForce GTX 460.

关键词： Qausi-Monte Carlo Gaussian particle filter parallel implementation CUDA

作者: Naigao Jin Feimo Li Zhaoxing Li

作者单位: School of Software, Dalian University of Technology,Dalian, 116620,P.R.China

会议类型: 国际会议

会议名称: 2011 3nd International Conference on Mechanical and Electronics Engineering(2011年第三届机械与电子工程国际会议 ICMEE2011)

会议地点: 合肥

会议语种:英文

页码: 3311-3315

在线出版日期: 2011-09-23（万方平台首次上网日期，不代表论文的发表时间）