{"title":"无线传感器网络中基于盲估计的多目标检测与定位","authors":"P. Zhang, Xiaoyong Deng, H. Wen, Jifu Guo","doi":"10.5220/0003464700610064","DOIUrl":null,"url":null,"abstract":"Observations of sensors are modeled as mixed signals in multiple targets scenario. Each element of mixing matrix represents the power decay of a pair of target and sensor, and each column preserves the waveform formed by the corresponding target respectively. Making use of blind estimation algorithms, we get the estimation of mixing matrix. Target locations are then estimated using the least squares method.","PeriodicalId":292305,"journal":{"name":"Proceedings of the International Conference on Wireless Information Networks and Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multiple targets detection and localization based on blind estimation in wireless sensor network\",\"authors\":\"P. Zhang, Xiaoyong Deng, H. Wen, Jifu Guo\",\"doi\":\"10.5220/0003464700610064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Observations of sensors are modeled as mixed signals in multiple targets scenario. Each element of mixing matrix represents the power decay of a pair of target and sensor, and each column preserves the waveform formed by the corresponding target respectively. Making use of blind estimation algorithms, we get the estimation of mixing matrix. Target locations are then estimated using the least squares method.\",\"PeriodicalId\":292305,\"journal\":{\"name\":\"Proceedings of the International Conference on Wireless Information Networks and Systems\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Wireless Information Networks and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0003464700610064\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Wireless Information Networks and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0003464700610064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiple targets detection and localization based on blind estimation in wireless sensor network
Observations of sensors are modeled as mixed signals in multiple targets scenario. Each element of mixing matrix represents the power decay of a pair of target and sensor, and each column preserves the waveform formed by the corresponding target respectively. Making use of blind estimation algorithms, we get the estimation of mixing matrix. Target locations are then estimated using the least squares method.
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