An Improved Particle Filtering Algorithm for Information Acquisition

摘要：

In this paper, we present an improved particle filtering algorithm called GUMPF for nonlinear, non-Gaussian and non-stationary state estimation problems in information acquisition field. The proposed algorithm integrates various virtues of current prevalent particle filters, and has satisfying filtering accuracy and numerical stability at acceptable computational cost. Simulation results show the feasibility and efficiency of the proposed algorithm compared with other related algorithms.

关键词： particle filter information acquisition Gaussian mixture model unscented Kalman filter Markov Chain Monte Carlo

作者: Jingxi Li Shuzong Wang Huadong Chen

作者单位: Institute for application Study to Modern Technology of Naval Weapon Naval University of Engineering Wuhan, Hubei Province, 430033, China

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 567-571

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）