{"title":"Positioning a time-varying number of targets by a wireless sensor network","authors":"P. Djuric, M. Bugallo, Jae-Chan Lim","doi":"10.1109/CAMAP.2005.1574193","DOIUrl":null,"url":null,"abstract":"In this paper we address the problem of positioning of multiple targets based on measurements obtained by sensors comprising a sensor network. The measurements represent a superposition of signals that carry information about the positions of the various targets. The sensors send the sensed information to a fusion center that combines the received data from all the sensors and carries out necessary computations. The number of targets may vary with time in an unknown way. We propose a particle filtering-based method for detecting the number of active targets and for estimating their positions. The particle filtering was carried out on data that represent measurements of acoustic signals, but it can also be applied to other types of signals. We provide simulations that show the performance of the particle filtering method in scenarios with one and two targets.","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMAP.2005.1574193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
In this paper we address the problem of positioning of multiple targets based on measurements obtained by sensors comprising a sensor network. The measurements represent a superposition of signals that carry information about the positions of the various targets. The sensors send the sensed information to a fusion center that combines the received data from all the sensors and carries out necessary computations. The number of targets may vary with time in an unknown way. We propose a particle filtering-based method for detecting the number of active targets and for estimating their positions. The particle filtering was carried out on data that represent measurements of acoustic signals, but it can also be applied to other types of signals. We provide simulations that show the performance of the particle filtering method in scenarios with one and two targets.