{"title":"H∞滤波算法在SINS/GPS组合导航系统中的应用","authors":"S. Wan-xin","doi":"10.1109/ICITEC.2014.7105575","DOIUrl":null,"url":null,"abstract":"H∞ filtering is a representative method of robust control. In the SINS/GPS integrated navigation system, to solve the limitation of Kalman in the system model and noise, this paper puts forward an application of H∞ filtering algorithm, which has strong robust performance in integrated navigation system. The filter equation of H∞ and Kalman algorithm is given. The integrated navigation (SINS/GPS) uses the output difference between SINS and GPS as input value of the filter, and then the error of integrated navigation system is estimated and corrected by one filtering method in real time. The accuracy and robustness are analyzed and compared between the two kinds of filtering algorithm. The simulation result shows that the H∞ filtering has better stability and robustness in colored noise. Through this research, H∞ filtering algorithm can well solve the uncertainty of the noise model and statistical characteristics. H∞ filtering algorithm is more suitable for the application of SINS/GPS to integrated navigation system.","PeriodicalId":293382,"journal":{"name":"Proceedings of 2nd International Conference on Information Technology and Electronic Commerce","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of H∞ filtering algorithm in SINS/GPS integrated navigation system\",\"authors\":\"S. Wan-xin\",\"doi\":\"10.1109/ICITEC.2014.7105575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"H∞ filtering is a representative method of robust control. In the SINS/GPS integrated navigation system, to solve the limitation of Kalman in the system model and noise, this paper puts forward an application of H∞ filtering algorithm, which has strong robust performance in integrated navigation system. The filter equation of H∞ and Kalman algorithm is given. The integrated navigation (SINS/GPS) uses the output difference between SINS and GPS as input value of the filter, and then the error of integrated navigation system is estimated and corrected by one filtering method in real time. The accuracy and robustness are analyzed and compared between the two kinds of filtering algorithm. The simulation result shows that the H∞ filtering has better stability and robustness in colored noise. Through this research, H∞ filtering algorithm can well solve the uncertainty of the noise model and statistical characteristics. H∞ filtering algorithm is more suitable for the application of SINS/GPS to integrated navigation system.\",\"PeriodicalId\":293382,\"journal\":{\"name\":\"Proceedings of 2nd International Conference on Information Technology and Electronic Commerce\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2nd International Conference on Information Technology and Electronic Commerce\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITEC.2014.7105575\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2nd International Conference on Information Technology and Electronic Commerce","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITEC.2014.7105575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of H∞ filtering algorithm in SINS/GPS integrated navigation system
H∞ filtering is a representative method of robust control. In the SINS/GPS integrated navigation system, to solve the limitation of Kalman in the system model and noise, this paper puts forward an application of H∞ filtering algorithm, which has strong robust performance in integrated navigation system. The filter equation of H∞ and Kalman algorithm is given. The integrated navigation (SINS/GPS) uses the output difference between SINS and GPS as input value of the filter, and then the error of integrated navigation system is estimated and corrected by one filtering method in real time. The accuracy and robustness are analyzed and compared between the two kinds of filtering algorithm. The simulation result shows that the H∞ filtering has better stability and robustness in colored noise. Through this research, H∞ filtering algorithm can well solve the uncertainty of the noise model and statistical characteristics. H∞ filtering algorithm is more suitable for the application of SINS/GPS to integrated navigation system.