{"title":"组合导航系统模糊自适应H∞鲁棒滤波器研究","authors":"Jiang Liu, Jian Wang, B. Cai","doi":"10.1109/ITSC.2008.4732653","DOIUrl":null,"url":null,"abstract":"This paper presents a novel integrated navigation algorithm based on the fuzzy adaptive Hinfin robust filter. By monitoring covariance between abstract and actual residual error, the definition of filtering performance factor is given. Based on the relationship between filtering performance factor, attenuation level and the parameter gamma in Hinfin robust filter, a fuzzy inference system is designed to choose gamma suitably and adaptively, so that there could be a balance between filtering accuracy and robustness performance accordingly. Analysis with practical train integrated navigation data validates the performance and practical value of the proposed algorithm.","PeriodicalId":184458,"journal":{"name":"International Conference on Intelligent Transportation Systems","volume":"19 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on Fuzzy Adaptive H∞ Robust Filter for Integrated Navigation System\",\"authors\":\"Jiang Liu, Jian Wang, B. Cai\",\"doi\":\"10.1109/ITSC.2008.4732653\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a novel integrated navigation algorithm based on the fuzzy adaptive Hinfin robust filter. By monitoring covariance between abstract and actual residual error, the definition of filtering performance factor is given. Based on the relationship between filtering performance factor, attenuation level and the parameter gamma in Hinfin robust filter, a fuzzy inference system is designed to choose gamma suitably and adaptively, so that there could be a balance between filtering accuracy and robustness performance accordingly. Analysis with practical train integrated navigation data validates the performance and practical value of the proposed algorithm.\",\"PeriodicalId\":184458,\"journal\":{\"name\":\"International Conference on Intelligent Transportation Systems\",\"volume\":\"19 6\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Intelligent Transportation Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2008.4732653\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2008.4732653","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Fuzzy Adaptive H∞ Robust Filter for Integrated Navigation System
This paper presents a novel integrated navigation algorithm based on the fuzzy adaptive Hinfin robust filter. By monitoring covariance between abstract and actual residual error, the definition of filtering performance factor is given. Based on the relationship between filtering performance factor, attenuation level and the parameter gamma in Hinfin robust filter, a fuzzy inference system is designed to choose gamma suitably and adaptively, so that there could be a balance between filtering accuracy and robustness performance accordingly. Analysis with practical train integrated navigation data validates the performance and practical value of the proposed algorithm.