Research on the unified robust Gaussian filters based on M-estimation

doi:10.23919/JSEE.2024.000116

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (5): 1161-1168.doi: 10.23919/JSEE.2024.000116

• ELECTRONICS TECHNOLOGY • Previous Articles

Research on the unified robust Gaussian filters based on M-estimation

Yunlong ZUO¹(), Xu LYU²^,*(), Xiaofeng ZHANG¹()

¹ College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China
² Department of Precision Instrument, Tsinghua University, Beijing 100084, China

Received:2023-12-14 Accepted:2024-09-27 Online:2025-10-18 Published:2025-10-24
Contact: Xu LYU E-mail:327731817@qq.com;lvclay@163.com;zhangxiaofeng201@126.com
About author:
ZUO Yunlong was born in 1988. He received his B.S. degree in electrical engineering and its automation in 2010 and M.S. degree in navigation, guidance and control in 2017 from the Naval University of Engineering, Wuhan, China, where he is currently working toward his Ph.D. degree with the Department of Electric Power System. His research interests include electric power system and its automation. E-mail: 327731817@qq.com

LYU Xu was born in 1990. He received his B.S. and M.S. degrees in control theory and control engineering from the Department of Electrical Engineering, Liaoning University of Technology, Jinzhou, China, in 2014 and 2019, respectively, and Ph.D. degree in navigation, guidance, and control from the Department of Navigation Engineering, Naval University of Engineering, Wuhan, China, in 2022. He is currently a postdoctoral fellow with the Department of Precision Instrument, Tsinghua University, Beijing, China. His main research interests include inertial navigation systems, integrated navigation, visual inertial navigation and cluster collaborative navigation and control. E-mail: lvclay@163.com

ZHANG Xiaofeng was born in 1963. He received his B.S. and M.S. degrees in electrical engineering from the Department of Navigation Engineering, Naval University of Engineering, Wuhan, China, and Ph.D. degree in electrical engineering from the Department of Electrical Engineering, Tsinghua University, Beijing, China. His research interests are in the field of ship electrical engineering and simulation technology. E-mail: zhangxiaofeng201@126.com
Supported by:
This work was supported by the Basic Science Center Program of the National Natural Science Foundation of China (62388101) and the National Natural Science Foundation of China (61873275).

Abstract

Abstract:

In this paper, the newly-derived maximum correntropy Kalman filter (MCKF) is re-derived from the M-estimation perspective, where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel function is a special case of many robust cost functions. Based on the derivation process, a unified form for the robust Gaussian filters (RGF) based on M-estimation is proposed to suppress the outliers and non-Gaussian noise in the measurement. The RGF provides a unified form for one Gaussian filter with different cost functions and a unified form for one robust filter with different approximating methods for the involved Gaussian integrals. Simulation results show that RGF with different weighting functions and different Gaussian integral approximation methods has robust anti-jamming performance.

Key words: maximum correntropy Kalman filter (MCKF), M-estimation, Gaussian filter

Yunlong ZUO, Xu LYU, Xiaofeng ZHANG. Research on the unified robust Gaussian filters based on M-estimation[J]. Journal of Systems Engineering and Electronics, 2025, 36(5): 1161-1168.

Figures/Tables 6

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Research on the unified robust Gaussian filters based on M-estimation

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