Multi-Kernel Maximum Correntropy Kalman Filter

被引：16

作者：

Li, Shilei ^{[1
]}

Shi, Dawei ^{[2
]}

Zou, Wulin ^{[1
,3
]}

Shi, Ling ^{[1
]}

机构：

[1] Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China

[2] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China

[3] Xeno Dynam Co Ltd, Control Dept, Shenzhen 518000, Peoples R China

来源：

IEEE CONTROL SYSTEMS LETTERS | 2022年 / 6卷

关键词：

Kernel; Kalman filters; Bandwidth; Noise measurement; Random variables; Pollution measurement; Covariance matrices; Multi-kernel correntropy; Kalman filter; non-Gaussian noises; disturbance;

D O I：

10.1109/LCSYS.2021.3114137

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Maximum correntropy criterion (MCC) has been widely used in Kalman filter to cope with heavy-tailed measurement noises. However, its performance on mitigating non-Gaussian process noises and unknown disturbance is rarely explored. In this letter, we extend the definition of correntropy from a single kernel to multiple kernels. Then, we derive a multi-kernel maximum correntropy Kalman filter (MKMCKF) to cope with multivariate non-Gaussian noises and disturbance. Three examples are provided to show the effectiveness of the proposed methods.

引用

页码：1490 / 1495

页数：6

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