{"title":"无人机多辐射源被动探测与跟踪控制","authors":"P. Sarunic, R. Evans, W. Moran","doi":"10.1109/CISDA.2009.5356551","DOIUrl":null,"url":null,"abstract":"An algorithm for trajectory optimization of autonomous aerial vehicles performing multiple target tracking is proposed. The problem is approached by formulating it as a partially observed Markov decision process (POMDP) and developing a moving-horizon solution taking into account short and long term costs. To evaluate the effectiveness of the approach a simulation involving multiple UAVs and targets is performed.","PeriodicalId":6407,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications","volume":"52 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Control of unmanned aerial vehicles for passive detection and tracking of multiple emitters\",\"authors\":\"P. Sarunic, R. Evans, W. Moran\",\"doi\":\"10.1109/CISDA.2009.5356551\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm for trajectory optimization of autonomous aerial vehicles performing multiple target tracking is proposed. The problem is approached by formulating it as a partially observed Markov decision process (POMDP) and developing a moving-horizon solution taking into account short and long term costs. To evaluate the effectiveness of the approach a simulation involving multiple UAVs and targets is performed.\",\"PeriodicalId\":6407,\"journal\":{\"name\":\"2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications\",\"volume\":\"52 1\",\"pages\":\"1-7\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISDA.2009.5356551\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISDA.2009.5356551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Control of unmanned aerial vehicles for passive detection and tracking of multiple emitters
An algorithm for trajectory optimization of autonomous aerial vehicles performing multiple target tracking is proposed. The problem is approached by formulating it as a partially observed Markov decision process (POMDP) and developing a moving-horizon solution taking into account short and long term costs. To evaluate the effectiveness of the approach a simulation involving multiple UAVs and targets is performed.
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