Centered Error Entropy-Based Variational Bayesian Adaptive and Robust Kalman Filter

被引：11

作者：

Yang, Baojian ^{[1
]}

Du, Binhan ^{[1
]}

Li, Ning ^{[2
]}

Li, Siyu ^{[1
]}

Shi, Zhiyong ^{[1
]}

机构：

[1] Army Engn Univ PLA, Dept Vehicle & Elect Engn, Shijiazhuang Campus, Shijiazhuang 050003, Hebei, Peoples R China

[2] Army Engn Univ PLA, Ordnance NCO Acad, Dept Equipment Chassis, Wuhan 430000, Peoples R China

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2022年 / 69卷 / 12期

关键词：

Adaptive Kalman filter; robust filter; centered error entropy; variational Bayesian;

D O I：

10.1109/TCSII.2022.3196452

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 brief, a centered error entropy based variational Bayesian adaptive and robust Kalman filter (CEEVBKF) is proposed to suppress outlier noise and estimate the unknown noise covariance adaptively. The derived CEEVBKF contains three steps: one-step prediction, centered error entropy (CEE) based outlier suppression, and variational Bayesian (VB) inference. The CEE criterion is first used to suppress outlier noise and obtain rough state estimation value, then they are set as a priori value in VB inference step for accurate a posteriori state estimation. The joint estimation of CEE and VB improves the iterative efficiency and reduces the parameter sensitivity. The simulation results show the effectiveness of CEEVBKF.

引用

页码：5179 / 5183

页数：5

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