Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation
To address the issues of low filtering accuracy and poor reliability encountered when employing the Sage-Husa adaptive filtering algorithm in combined navigation systems, an improved Sage-Husa adaptive filtering algorithm is proposed. Firstly, on the basis of the Sage-Husa adaptive filtering algori...
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2024-06-01
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| Series: | Journal of Harbin University of Science and Technology |
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| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2329 |
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| author | WEN Sheng LIU Caiyun LUAN Tiantian SUN Mingxiao |
| author_facet | WEN Sheng LIU Caiyun LUAN Tiantian SUN Mingxiao |
| author_sort | WEN Sheng |
| collection | DOAJ |
| description | To address the issues of low filtering accuracy and poor reliability encountered when employing the Sage-Husa adaptive filtering algorithm in combined navigation systems, an improved Sage-Husa adaptive filtering algorithm is proposed. Firstly, on the basis of the Sage-Husa adaptive filtering algorithm, the statistical characteristics of noise are estimated by the weighted estimation method of exponential fading memory to improve the adaptive ability of the algorithm. Then, by the introduction of the fading factor in the strong tracking filtering, the prediction mean-square error matrix is corrected online, so that the improved algorithm has the ability to cope with the uncertainties such as systematic error interference. Simulation results demonstrate that the improved Sage-Husa algorithm exhibits greater adaptive ability. It effectively suppresses filter divergence and maintains excellent filtering performance, even when faced with model error and coarse interference. Furthermore, when applied in combined navigation systems, the algorithm showcases improved stability and positioning accuracy. |
| format | Article |
| id | doaj-art-aa80d554bf894cf5a9bbfb67ac1b3179 |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2024-06-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-aa80d554bf894cf5a9bbfb67ac1b31792025-08-20T03:28:21ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832024-06-012903374410.15938/j.jhust.2024.03.005Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated NavigationWEN Sheng0LIU Caiyun1LUAN Tiantian2SUN Mingxiao3School of Automation,Harbin University of Science and Technology,Harbin 150080 ,ChinaSchool of Automation,Harbin University of Science and Technology,Harbin 150080 ,ChinaSchool of Automation,Harbin University of Science and Technology,Harbin 150080 ,ChinaSchool of Automation,Harbin University of Science and Technology,Harbin 150080 ,ChinaTo address the issues of low filtering accuracy and poor reliability encountered when employing the Sage-Husa adaptive filtering algorithm in combined navigation systems, an improved Sage-Husa adaptive filtering algorithm is proposed. Firstly, on the basis of the Sage-Husa adaptive filtering algorithm, the statistical characteristics of noise are estimated by the weighted estimation method of exponential fading memory to improve the adaptive ability of the algorithm. Then, by the introduction of the fading factor in the strong tracking filtering, the prediction mean-square error matrix is corrected online, so that the improved algorithm has the ability to cope with the uncertainties such as systematic error interference. Simulation results demonstrate that the improved Sage-Husa algorithm exhibits greater adaptive ability. It effectively suppresses filter divergence and maintains excellent filtering performance, even when faced with model error and coarse interference. Furthermore, when applied in combined navigation systems, the algorithm showcases improved stability and positioning accuracy.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2329integrated navigationsage-husa adaptive filteringattenuation factorstrong tracking filteringnoise estimation; model error |
| spellingShingle | WEN Sheng LIU Caiyun LUAN Tiantian SUN Mingxiao Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation Journal of Harbin University of Science and Technology integrated navigation sage-husa adaptive filtering attenuation factor strong tracking filtering noise estimation; model error |
| title | Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation |
| title_full | Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation |
| title_fullStr | Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation |
| title_full_unstemmed | Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation |
| title_short | Application of Improved Sage-Husa Algorithm in SINS/GPS Integrated Navigation |
| title_sort | application of improved sage husa algorithm in sins gps integrated navigation |
| topic | integrated navigation sage-husa adaptive filtering attenuation factor strong tracking filtering noise estimation; model error |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2329 |
| work_keys_str_mv | AT wensheng applicationofimprovedsagehusaalgorithminsinsgpsintegratednavigation AT liucaiyun applicationofimprovedsagehusaalgorithminsinsgpsintegratednavigation AT luantiantian applicationofimprovedsagehusaalgorithminsinsgpsintegratednavigation AT sunmingxiao applicationofimprovedsagehusaalgorithminsinsgpsintegratednavigation |