{"title":"卡尔曼滤波在三颗北斗静止卫星无源动态定位中的应用","authors":"Wu Xiao-dong, Wu Si-liang, Wang Ju, Liang Jia-qi","doi":"10.1109/ICOSP.2008.4697138","DOIUrl":null,"url":null,"abstract":"Aimed at the movement model of Three Beidou Geostationary Satellites passive dynamic positioning receiver and the noise characteristics of the receiving signal, the turn model is applied to represent exactly the movement pattern of the receiver, and a Kalman filter algorithm based on turn model is presented in this paper. By filtering the Three Beidou Geostationary Satellites passive dynamic positioning results, the emulation experiment shows that the algorithm can eliminate most random errors in the dynamic positioning. Compared with the traditional Kalman filter algorithms, the algorithm presented in this paper is charactered with easy realization, well application and high positioning precision, and a good result is obtained in the practical application.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of Kalman filter in Three Beidou Geostationary Satellites passive dynamic positioning\",\"authors\":\"Wu Xiao-dong, Wu Si-liang, Wang Ju, Liang Jia-qi\",\"doi\":\"10.1109/ICOSP.2008.4697138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aimed at the movement model of Three Beidou Geostationary Satellites passive dynamic positioning receiver and the noise characteristics of the receiving signal, the turn model is applied to represent exactly the movement pattern of the receiver, and a Kalman filter algorithm based on turn model is presented in this paper. By filtering the Three Beidou Geostationary Satellites passive dynamic positioning results, the emulation experiment shows that the algorithm can eliminate most random errors in the dynamic positioning. Compared with the traditional Kalman filter algorithms, the algorithm presented in this paper is charactered with easy realization, well application and high positioning precision, and a good result is obtained in the practical application.\",\"PeriodicalId\":445699,\"journal\":{\"name\":\"2008 9th International Conference on Signal Processing\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 9th International Conference on Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.2008.4697138\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 9th International Conference on Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2008.4697138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Kalman filter in Three Beidou Geostationary Satellites passive dynamic positioning
Aimed at the movement model of Three Beidou Geostationary Satellites passive dynamic positioning receiver and the noise characteristics of the receiving signal, the turn model is applied to represent exactly the movement pattern of the receiver, and a Kalman filter algorithm based on turn model is presented in this paper. By filtering the Three Beidou Geostationary Satellites passive dynamic positioning results, the emulation experiment shows that the algorithm can eliminate most random errors in the dynamic positioning. Compared with the traditional Kalman filter algorithms, the algorithm presented in this paper is charactered with easy realization, well application and high positioning precision, and a good result is obtained in the practical application.