Home Journals Articles Updates About
CN
image
收藏切换
Non-Equal-Weighted Maximum Correntropy Filtering Algorithm for the GNSS/SINS Integrated Navigation System
收藏切换
Siming LIU1, Xueyuan LIN2, Yuxin QIAO1, *
Journal of Geodesy and Geodynamics | 2026, 46(7) : 816 - 824
Less
收藏切换
Journal of Geodesy and Geodynamics | 2026, 46(7): 816-824
Non-Equal-Weighted Maximum Correntropy Filtering Algorithm for the GNSS/SINS Integrated Navigation System
Full
Siming LIU1, Xueyuan LIN2, Yuxin QIAO1, *
Affiliations
  • 1 College of Intelligent Science and Engineering, Yantai Nanshan University, Yantai 265713, China
  • 2 School of Artificial Intelligence, Shandong Vocational University of Foreign Affairs, Weihai 264500, China
Published: 2026-07-15 doi: 10.14075/j.jgg.2025.11.399
Outline
收藏切换

In the maximum correntropy Kalman filter based on equal weighting (MCKF), since the error samples with different qualities are weighted equally, it affects the filtering accuracy of the GNSS/SINS integrated navigation system based on MCKF. To solve this problem, a non-equal-weighted maximum correntropy Kalman filter (NWMCKF) is proposed. Firstly, based on the equal weighting maximum correntropy criterion (MCC), a non-equal-weighted maximum correntropy criterion (NWMCC) is proposed to reduce the adverse effects caused by MCC applying the same weight to all error samples. Then, based on NWMCC, the algorithm equation of NWMCKF is derived, and the fixed-point iterative recursive algorithm flow of NWMCKF is given. Finally, experiments on the GNSS/SINS integrated navigation system based on KF, MCKF and NWMCKF are carried out for verification. The experimental results show that when the measurement noise is Gaussian noise, the filtering performance of NWMCKF is slightly better than that of MCKF; when the measurement noise is non-Gaussian noise, the filtering performance of NWMCKF is significantly better than that of MCKF.

non-equal-weighted maximum correlation entropy criterion(NWMCC)  /  non-equal-weighted maximum correlation entropy Kalman filter(NWMCKF)  /  integrated navigation  /  fixed-point iterative recursive algorithm
刘思明, 林雪原, 乔玉新. GNSS/SINS组合导航系统的非等加权最大相关熵滤波算法. 大地测量与地球动力学, 2026 , 46 (7) : 816 -824 . DOI: 10.14075/j.jgg.2025.11.399
Siming LIU, Xueyuan LIN, Yuxin QIAO. Non-Equal-Weighted Maximum Correntropy Filtering Algorithm for the GNSS/SINS Integrated Navigation System[J]. Journal of Geodesy and Geodynamics, 2026 , 46 (7) : 816 -824 . DOI: 10.14075/j.jgg.2025.11.399
Appendix
Less
Year 2026 volume 46 Issue 7
34
13
Cite this Article
BibTeX
Article Info
doi: 10.14075/j.jgg.2025.11.399
  • Receive Date：2025-11-20
  • Online Date：2026-10-30
  • Published：2026-07-15
Article Data
Affiliations
History
  • Received：2025-11-20
Funding
Affiliations
    1 College of Intelligent Science and Engineering, Yantai Nanshan University, Yantai 265713, China
    2 School of Artificial Intelligence, Shandong Vocational University of Foreign Affairs, Weihai 264500, China
References
Share
https://castjournals.cast.org.cn/joweb/ddcl/EN/10.14075/j.jgg.2025.11.399
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House