Yandong Wang, Shaoshuai Yang, Huafeng Hu, Kui Chen, Qingchang Ji
{"title":"基于鲁棒滤波的无人机编队相对导航算法","authors":"Yandong Wang, Shaoshuai Yang, Huafeng Hu, Kui Chen, Qingchang Ji","doi":"10.1109/ICCECT.2012.178","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of determination of the relative position and the relative velocity of formation flight unmanned aerial vehicles, the relative navigation algorithm based on H∞ filter with non-Gaussian noise input and the system model parameter uncertainty is developed. The system investigated here consists of two Inertial Navigation systems, ranging Radar and Vision sensor. The necessary and sufficient existence condition of desired estimator and its design method are solved by convex optimization based on linear matrix inequality. Numerical simulation results show that the filtering algorithm has a valid estimate of the relative status between the two machines when Kalman filter does not work as good in the case of non-Gaussian noise and system model uncertainty.","PeriodicalId":153613,"journal":{"name":"2012 International Conference on Control Engineering and Communication Technology","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Relative Navigation Algorithm Based on Robust Filter for UAV Formation Flight\",\"authors\":\"Yandong Wang, Shaoshuai Yang, Huafeng Hu, Kui Chen, Qingchang Ji\",\"doi\":\"10.1109/ICCECT.2012.178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problem of determination of the relative position and the relative velocity of formation flight unmanned aerial vehicles, the relative navigation algorithm based on H∞ filter with non-Gaussian noise input and the system model parameter uncertainty is developed. The system investigated here consists of two Inertial Navigation systems, ranging Radar and Vision sensor. The necessary and sufficient existence condition of desired estimator and its design method are solved by convex optimization based on linear matrix inequality. Numerical simulation results show that the filtering algorithm has a valid estimate of the relative status between the two machines when Kalman filter does not work as good in the case of non-Gaussian noise and system model uncertainty.\",\"PeriodicalId\":153613,\"journal\":{\"name\":\"2012 International Conference on Control Engineering and Communication Technology\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Control Engineering and Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECT.2012.178\",\"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 International Conference on Control Engineering and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECT.2012.178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Relative Navigation Algorithm Based on Robust Filter for UAV Formation Flight
In order to solve the problem of determination of the relative position and the relative velocity of formation flight unmanned aerial vehicles, the relative navigation algorithm based on H∞ filter with non-Gaussian noise input and the system model parameter uncertainty is developed. The system investigated here consists of two Inertial Navigation systems, ranging Radar and Vision sensor. The necessary and sufficient existence condition of desired estimator and its design method are solved by convex optimization based on linear matrix inequality. Numerical simulation results show that the filtering algorithm has a valid estimate of the relative status between the two machines when Kalman filter does not work as good in the case of non-Gaussian noise and system model uncertainty.