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Academic article

Integrated Navigation Maximum Correntropy Filtering Algorithm with Adaptive Kernel Bandwidth

  • LIN Xueyuan , 1 ,
  • PAN Xinlong , 2, * ,
  • ZHU Zhenqiu 3 ,
  • LI Shufeng 1
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  • 1 School of Artificial Intelligence,Shandong Vocational University of Foreign Affairs,Weihai 264500,Shandong,China
  • 2 Institute of Information Fusion,Naval Aeronautical University,Yantai 264500,Shandong,China
  • 3 The 32006 Unit of the People’s Liberation Army,Beijing 100000,China

Received date: 2025-05-16

  Online published: 2026-01-24

Abstract

Maximum correntropy Kalman filter (MCKF) can improve the filtering accuracy of integrated navigation system in complex environment,but MCKF with fixed kernel bandwidth may cause the filtering accuracy to decrease.Therefore,how to correctly select the kernel width is a key problem in MCKF.In this paper,an adaptive factor is constructed according to the filter innovation and its theoretical covariance,and the kernel bandwidth is adjusted online according to the adaptive factor and the selected maximum kernel bandwidth to eliminate the influence of kernel bandwidth on MCKF performance,and then an adaptive kernel MCCKF (AMCCKF) is proposed.The GNSS/SINS integrated navigation system is used to verify the AMCCKF.The experimental results show that AMCCKF has the ability to adjust the kernel bandwidth on line and obtain the optimal value of the kernel bandwidth quickly.Compared with the conventional Kalman Filter (KF) and the highly robust MCKF (with a Kernal bandwidth of 2.5),AMCKF can improve the position accuracy by approximately 55.5% and 24.1% respectively,and the velocity accuracy by approximately 34.9% and 27.7% respectively.

Cite this article

LIN Xueyuan , PAN Xinlong , ZHU Zhenqiu , LI Shufeng . Integrated Navigation Maximum Correntropy Filtering Algorithm with Adaptive Kernel Bandwidth[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2025 , 45(6) : 1303 -1309 . DOI: 10.15892/j.cnki.djzdxb.2025.06.042

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