{"title":"基于低轨道卫星数学模型的传感器融合","authors":"S. Kartal, Tayfun Dar","doi":"10.31590/ejosat.1216679","DOIUrl":null,"url":null,"abstract":"In this study, the mathematical model of attitude motion is obtained for low orbit sattelite (LEO) with its kinematic and dynamic equations. The mathematical model of orbit motion for LEO satellite is obtained using Kepler parameters. Sensor data are generated adding zero mean Gaussian noise to data comes from model response. These measurement data are fused using INS/GPS integration structure. Extended Kalman filter algorithm is used to sensor fusion. Compare the estimated data comes from extended Kalman filter and the actual data generated from mathematical model. It has been observed from the results that the estimated data is closest to the actual attitude data. All study is performed at the MATLAB/Simulink environment.","PeriodicalId":12068,"journal":{"name":"European Journal of Science and Technology","volume":"43 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sensor Fusion Based on Mathematical Model of LEO Satellite\",\"authors\":\"S. Kartal, Tayfun Dar\",\"doi\":\"10.31590/ejosat.1216679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, the mathematical model of attitude motion is obtained for low orbit sattelite (LEO) with its kinematic and dynamic equations. The mathematical model of orbit motion for LEO satellite is obtained using Kepler parameters. Sensor data are generated adding zero mean Gaussian noise to data comes from model response. These measurement data are fused using INS/GPS integration structure. Extended Kalman filter algorithm is used to sensor fusion. Compare the estimated data comes from extended Kalman filter and the actual data generated from mathematical model. It has been observed from the results that the estimated data is closest to the actual attitude data. All study is performed at the MATLAB/Simulink environment.\",\"PeriodicalId\":12068,\"journal\":{\"name\":\"European Journal of Science and Technology\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31590/ejosat.1216679\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31590/ejosat.1216679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sensor Fusion Based on Mathematical Model of LEO Satellite
In this study, the mathematical model of attitude motion is obtained for low orbit sattelite (LEO) with its kinematic and dynamic equations. The mathematical model of orbit motion for LEO satellite is obtained using Kepler parameters. Sensor data are generated adding zero mean Gaussian noise to data comes from model response. These measurement data are fused using INS/GPS integration structure. Extended Kalman filter algorithm is used to sensor fusion. Compare the estimated data comes from extended Kalman filter and the actual data generated from mathematical model. It has been observed from the results that the estimated data is closest to the actual attitude data. All study is performed at the MATLAB/Simulink environment.
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