Unified Form for the Robust Gaussian Information Filtering Based on M-Estimate

被引：70

作者：

Chang, Lubin ^{[1
]}

Li, Kailong ^{[1
]}

机构：

[1] Naval Univ Engn, Dept Nav Engn, Wuhan 430033, Peoples R China

来源：

IEEE SIGNAL PROCESSING LETTERS | 2017年 / 24卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Gaussian approximate; heavy-tailed noise; information filtering; M-estimate; KALMAN FILTER; TRACKING;

D O I：

10.1109/LSP.2017.2669238

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a unified form for robust Gaussian information filtering based onM-estimate is proposed, which can incorporate robust weight functions with zero weight for large residues. The proposed information filtering framework can avoid the numerical problem introduced by the zero weight in the Kalman filtering framework. Simulation results show the efficiency and superiority of the proposed robust filters over the nonrobust filter against heavy-tailed measurement noises.

引用

页码：412 / 416

页数：5

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