Adaptive unscented particle filter algorithm under unknown noise

doi:10.7964/jdxbgxb201304047

	Adaptive unscented particle filter algorithm under unknown noise
	Li, Yu-Chen 1,2; Li, Zhan-Ming1
	2013-07-01
发表期刊	Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)
ISSN	16715497
卷号	43 期号:4 页码:1139-1145
摘要	In order to solve the target tracking problem when the statistic characteristics of the system are unknown, an adaptive unscented particle filter algorithm is proposed. This algorithm estimates and corrects the statistic characteristics of the unknown system noise in real-time using improved Sage-Husa estimator. Combining with unscented Kalman filter, the algorithm produces the optimal proposal distribution function. This method effectively reduces the estimation error and improves the anti-noise ability of the system. Theoretical analysis and experiments show that the new method can significantly improve the accuracy and stability of target tracking when the statistic characteristics of the system are unknown.
关键词	Adaptive filters Clutter (information theory) Data processing Distribution functions Information filtering Kalman filters Monte Carlo methods Target tracking Anti-noise ability Estimation errors Particle filter Proposal distribution Statistic characteristics Unknown noise Unscented Kalman Filter Unscented particle filters
DOI	10.7964/jdxbgxb201304047
收录类别	EI
语种	中文
出版者	Editorial Board of Jilin University
EI入藏号	20133216588360
EI主题词	Adaptive filtering
EI分类号	716.1 Information Theory and Signal Processing - 723.2 Data Processing and Image Processing - 903.1 Information Sources and Analysis - 922.1 Probability Theory - 922.2 Mathematical Statistics
来源库	Compendex
分类代码	716.1 Information Theory and Signal Processing - 723.2 Data Processing and Image Processing - 903.1 Information Sources and Analysis - 922.1 Probability Theory - 922.2 Mathematical Statistics
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/113649
专题	电气工程与信息工程学院
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2.Key Laboratory of Advanced Control of Industrial Processes of Gansu Province, Lanzhou 730050, China
第一作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Li, Yu-Chen,Li, Zhan-Ming. Adaptive unscented particle filter algorithm under unknown noise[J]. Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition),2013,43(4):1139-1145.
APA	Li, Yu-Chen,&Li, Zhan-Ming.(2013).Adaptive unscented particle filter algorithm under unknown noise.Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition),43(4),1139-1145.
MLA	Li, Yu-Chen,et al."Adaptive unscented particle filter algorithm under unknown noise".Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) 43.4(2013):1139-1145.