Robust M-estimation-based maximum correntropy Kalman filter

被引:25
作者
Liu, Chen [1 ]
Wang, Gang [1 ]
Guan, Xin [1 ]
Huang, Chutong [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Peoples R China
关键词
Kalman filter; Robust regression; Maximum correntropy criterion; M-estimation; Non-Gaussian noises; SYSTEMS; FUSION;
D O I
10.1016/j.isatra.2022.10.025
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a framework that combines an M-estimation and information-theoretic-learning (ITL)based Kalman filter under impulsive noises is presented. The ITL-based methods make the most of the features of the data itself and can improve robustness by choosing an appropriate kernel bandwidth. However, small kernel bandwidths may lead to divergence. Nonetheless, robust-regression methods can improve the robustness from the statistical perspective and are independent of kernel bandwidth. This motivates us to fuse M-estimation-based weighting methods and the ITL-based Kalman filter. The proposed framework inhibits the divergence trend of ITL-based Kalman filters at low kernel bandwidth and improves the performance at large kernel bandwidth. Additionally, we use the unscented Kalman filtering method to extend the proposed algorithm to the nonlinear case. Monte Carlo simulations demonstrate the robustness and effectiveness of the proposed algorithm. (c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:198 / 209
页数:12
相关论文
共 31 条
[1]  
Astle YS, 2017, IEEE INT CONF BIG DA, P1381, DOI 10.1109/BigData.2017.8258071
[2]  
Bilik I, 2006, IEEE INT C AC SPEECH, P724
[3]   Minimum Error Entropy Kalman Filter [J].
Chen, Badong ;
Dang, Lujuan ;
Gu, Yuantao ;
Zheng, Nanning ;
Principe, Jose C. .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (09) :5819-5829
[4]   Maximum correntropy Kalman filter [J].
Chen, Badong ;
Liu, Xi ;
Zhao, Haiquan ;
Principe, Jose C. .
AUTOMATICA, 2017, 76 :70-77
[5]   On the Tracking Performance of Adaptive Filters and Their Combinations [J].
Claser, Raffaello ;
Nascimento, Vitor H. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2021, 69 :3104-3116
[6]   A KNN-Based Radar Detector for Coherent Targets in Non-Gaussian Noise [J].
Coluccia, Angelo ;
Fascista, Alessio ;
Ricci, Giuseppe .
IEEE SIGNAL PROCESSING LETTERS, 2021, 28 :778-782
[7]   Unmanned aerial vehicle for transmission line inspection using an extended Kalman filter with colored electromagnetic interference [J].
da Silva, Mathaus Ferreira ;
Honorio, Leonardo M. ;
Marcato, Andre Luis M. ;
Vidal, Vinicius F. ;
Santos, Murillo F. .
ISA TRANSACTIONS, 2020, 100 :322-333
[8]   UKF Based on Maximum Correntropy Criterion in the Presence of Both Intermittent Observations and Non-Gaussian Noise [J].
Deng, Zhihong ;
Shi, Lei ;
Yin, Lijian ;
Xia, Yuanqing ;
Huo, Baoyu .
IEEE SENSORS JOURNAL, 2020, 20 (14) :7766-7773
[9]   ROBUST REGRESSION-BASED EKF FOR TRACKING UNDERWATER TARGETS [J].
ELHAWARY, F ;
JING, YY .
IEEE JOURNAL OF OCEANIC ENGINEERING, 1995, 20 (01) :31-41
[10]   Interacting Multiple Model Based on Maximum Correntropy Kalman Filter [J].
Fan, Xuxiang ;
Wang, Gang ;
Han, Jiachen ;
Wang, Yinghui .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2021, 68 (08) :3017-3021