{"title":"利用星载GPS导航传感器自主确定LEO轨道","authors":"S. Aghav, S. Gangal","doi":"10.1109/ISPTS.2012.6260882","DOIUrl":null,"url":null,"abstract":"In this paper, a simple but fairly accurate algorithm, to determine orbit of the Low Earth Orbit (LEO) satellite, in its real time and with low computational burden is reported. This is done by using raw navigation solution provided by GPS Navigation sensor. A fixed step-size Runge-Kutta 4th order numerical integration method is selected for orbit propagation. Both, the Least square and Extended Kalman Filter (EKF) orbit estimation algorithms are developed and the results of the same are compared with each other. The least square algorithm converges after seven iterations. In the case of EKF, the algorithm converges after three iterations. Hence, EKF algorithm satisfies the criterions of low computation burden which is required for autonomous orbit determination.","PeriodicalId":6431,"journal":{"name":"2012 1st International Symposium on Physics and Technology of Sensors (ISPTS-1)","volume":"110 1","pages":"70-73"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Use of spaceborne GPS Navigation sensor for autonomous LEO orbit determination\",\"authors\":\"S. Aghav, S. Gangal\",\"doi\":\"10.1109/ISPTS.2012.6260882\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a simple but fairly accurate algorithm, to determine orbit of the Low Earth Orbit (LEO) satellite, in its real time and with low computational burden is reported. This is done by using raw navigation solution provided by GPS Navigation sensor. A fixed step-size Runge-Kutta 4th order numerical integration method is selected for orbit propagation. Both, the Least square and Extended Kalman Filter (EKF) orbit estimation algorithms are developed and the results of the same are compared with each other. The least square algorithm converges after seven iterations. In the case of EKF, the algorithm converges after three iterations. Hence, EKF algorithm satisfies the criterions of low computation burden which is required for autonomous orbit determination.\",\"PeriodicalId\":6431,\"journal\":{\"name\":\"2012 1st International Symposium on Physics and Technology of Sensors (ISPTS-1)\",\"volume\":\"110 1\",\"pages\":\"70-73\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 1st International Symposium on Physics and Technology of Sensors (ISPTS-1)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPTS.2012.6260882\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 1st International Symposium on Physics and Technology of Sensors (ISPTS-1)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPTS.2012.6260882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Use of spaceborne GPS Navigation sensor for autonomous LEO orbit determination
In this paper, a simple but fairly accurate algorithm, to determine orbit of the Low Earth Orbit (LEO) satellite, in its real time and with low computational burden is reported. This is done by using raw navigation solution provided by GPS Navigation sensor. A fixed step-size Runge-Kutta 4th order numerical integration method is selected for orbit propagation. Both, the Least square and Extended Kalman Filter (EKF) orbit estimation algorithms are developed and the results of the same are compared with each other. The least square algorithm converges after seven iterations. In the case of EKF, the algorithm converges after three iterations. Hence, EKF algorithm satisfies the criterions of low computation burden which is required for autonomous orbit determination.