Particle filter algorithm with correlative noises | |
Li, Wei; Cao, Jie![]() ![]() ![]() | |
2016-05-30 | |
发表期刊 | Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China
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ISSN | 10010548 |
卷号 | 45期号:3页码:436-441 |
摘要 | The standard particle filter needs to meet the requirement of noise independent. In order to overcome this limitation, this paper proposes a correlative noise particle filter (CN-PF) algorithm. The method analyzes the characteristic of noise time correlation, and derives the joint probability density function of correlative noise based on the given nonlinear system model. The concrete implementation method of noise de-correlation is analyzed based on the Gaussian noise assumption. The optimal proposal distribution function is deduced in the condition of the importance weight variance minimum. The CN-PF algorithm compensates the shortage of the traditional particle filter algorithm effectively, and expands the application range of the PF algorithm. The theoretical analysis and simulation results show the effectiveness of the propose method. © 2016, Editorial Board of Journal of the University of Electronic Science and Technology of China. All right reserved. |
关键词 | Distribution functions Monte Carlo methods Nonlinear systems Probability density function Analysis and simulation Characteristic of noise Joint probability density function Noise correlation Nonlinear system modeling Particle filter Particle filter algorithms Proposal distribution |
DOI | 10.3969/j.issn.1001-0548.2016.02.021 |
收录类别 | EI |
语种 | 中文 |
出版者 | Univ. of Electronic Science and Technology of China |
EI入藏号 | 20162202444248 |
EI主题词 | Gaussian noise (electronic) |
EI分类号 | 922.1 Probability Theory - 922.2 Mathematical Statistics - 961 Systems Science |
来源库 | Compendex |
分类代码 | 922.1 Probability Theory - 922.2 Mathematical Statistics - 961 Systems Science |
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/112488 |
专题 | 理学院 电气工程与信息工程学院 |
作者单位 | College of Electrical and Information Engineering, Lanzhou University of Technology, 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, Wei,Cao, Jie,Li, Jun,et al. Particle filter algorithm with correlative noises[J]. Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China,2016,45(3):436-441. |
APA | Li, Wei,Cao, Jie,Li, Jun,&Wang, Jin-Hua.(2016).Particle filter algorithm with correlative noises.Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China,45(3),436-441. |
MLA | Li, Wei,et al."Particle filter algorithm with correlative noises".Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China 45.3(2016):436-441. |
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