{"title":"航空器识别用状态估计方法","authors":"Lorand Lukacs","doi":"10.1109/SACI.2014.6840090","DOIUrl":null,"url":null,"abstract":"The study presents a state estimation method for the determination of an aircraft's position, speed, spatial orientation and angular velocity based on the data fusion of differential GPS, 3D accelerometer, angular velocity and magnetometer sensors and Extended Kalman Filtering on actual flight data. The paper also proposes a method for determining the aircraft's angle of attack and sideslip angles. The state variables together with the aircraft's actuator signals (determined separately) are considered as input signals for the identification of an aircraft's nonlinear model.","PeriodicalId":163447,"journal":{"name":"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"State estimation method for aircraft identification purposes\",\"authors\":\"Lorand Lukacs\",\"doi\":\"10.1109/SACI.2014.6840090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The study presents a state estimation method for the determination of an aircraft's position, speed, spatial orientation and angular velocity based on the data fusion of differential GPS, 3D accelerometer, angular velocity and magnetometer sensors and Extended Kalman Filtering on actual flight data. The paper also proposes a method for determining the aircraft's angle of attack and sideslip angles. The state variables together with the aircraft's actuator signals (determined separately) are considered as input signals for the identification of an aircraft's nonlinear model.\",\"PeriodicalId\":163447,\"journal\":{\"name\":\"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2014.6840090\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 9th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2014.6840090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
State estimation method for aircraft identification purposes
The study presents a state estimation method for the determination of an aircraft's position, speed, spatial orientation and angular velocity based on the data fusion of differential GPS, 3D accelerometer, angular velocity and magnetometer sensors and Extended Kalman Filtering on actual flight data. The paper also proposes a method for determining the aircraft's angle of attack and sideslip angles. The state variables together with the aircraft's actuator signals (determined separately) are considered as input signals for the identification of an aircraft's nonlinear model.