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An improved particle filtering algorithm based on observation inversion optimal sampling
Abstract：According to the effective sampling of particles and the particles impoverishment caused by re-sampling in particle filter, an improved particle filtering algorithm based on observation inversion optimal sampling was proposed. Firstly, virtual observations were generated from the latest observation, and two sampling strategies were presented. Then, the previous time particles were sampled by utilizing the function inversion relationship between observation and system state. Finally, the current time particles were generated on the basis of the previous time particles and the system one-step state transition model. By the above method, sampling particles can make full use of the latest observation information and the priori modeling information, so that they further approximate the true state. The theoretical analysis and experimental results show that the new algorithm filtering accuracy and real-time outperform obviously the standard particle filter, the extended Kalman particle filter and the unscented particle filter. 作者： Author： HU Zhen-tao PAN Quan YANG Feng CHENG Yong-mei 作者单位： College of Automation, Northwestern Polytechnical University, Xian 710072, China 期 刊： 中南大学学报（英文版） EISCI Journal： JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY(ENGLISH EDITION) 年，卷(期)： 2009, 16(5) 分类号： Keywords： particle filter proposal distribution re-sampling observation inversion 机标分类号： V24 TN9 机标关键词： based filtering algorithm particle filter information sampling strategies real-time state transition new algorithm relationship effective one-step modeling improved function extended analysis results Kalman basis make 基金项目： the Key Project of the National Natural Science Foundation of China，国家自然科学基金，Aviation Science Foundation of China，the Space-Flight Innovation Foundation of China An improved particle filtering algorithm based on observation inversion optimal sampling[期刊论文] 中南大学学报（英文版） --2009, 16(5)According to the effective sampling of particles and the particles impoverishment caused by re-sampling in particle filter, an improved particle filtering algorithm based on observation inversion optim...【An improved particle filtering algor】相关文章：
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