{"title":"无线网络中基于接收信号强度定位的分布式线性组合估计","authors":"Wei-Yu Chen, Scott L. Miller","doi":"10.1109/CISS.2009.5054727","DOIUrl":null,"url":null,"abstract":"Wireless geolocation problems based on received signal strength (RSS) are discussed in this paper. Using the maximum likelihood based range estimates, a new distributed and iterative linear combination location estimator is proposed. In a non-cooperative case where unknown-location (blindfolded) devices only utilize the power measurements from known-location devices (anchors), the proposed algorithm has a similar error performance to the maximum likelihood estimator but the computation time is much less. In cooperative localization, a blindfolded node uses information from not only anchors but also other blindfolded nodes. After being compared with the distributed maximum likelihood estimator and the distributed weighted-multidimensional scaling (dwMDS) method, it is recognized that the estimator performs well in accuracy, computation time, and the use of wireless transmissions under various wireless environments.","PeriodicalId":433796,"journal":{"name":"2009 43rd Annual Conference on Information Sciences and Systems","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Distributed linear combination estimators for localization based on received signal strength in wireless networks\",\"authors\":\"Wei-Yu Chen, Scott L. Miller\",\"doi\":\"10.1109/CISS.2009.5054727\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless geolocation problems based on received signal strength (RSS) are discussed in this paper. Using the maximum likelihood based range estimates, a new distributed and iterative linear combination location estimator is proposed. In a non-cooperative case where unknown-location (blindfolded) devices only utilize the power measurements from known-location devices (anchors), the proposed algorithm has a similar error performance to the maximum likelihood estimator but the computation time is much less. In cooperative localization, a blindfolded node uses information from not only anchors but also other blindfolded nodes. After being compared with the distributed maximum likelihood estimator and the distributed weighted-multidimensional scaling (dwMDS) method, it is recognized that the estimator performs well in accuracy, computation time, and the use of wireless transmissions under various wireless environments.\",\"PeriodicalId\":433796,\"journal\":{\"name\":\"2009 43rd Annual Conference on Information Sciences and Systems\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 43rd Annual Conference on Information Sciences and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISS.2009.5054727\",\"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 43rd Annual Conference on Information Sciences and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISS.2009.5054727","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed linear combination estimators for localization based on received signal strength in wireless networks
Wireless geolocation problems based on received signal strength (RSS) are discussed in this paper. Using the maximum likelihood based range estimates, a new distributed and iterative linear combination location estimator is proposed. In a non-cooperative case where unknown-location (blindfolded) devices only utilize the power measurements from known-location devices (anchors), the proposed algorithm has a similar error performance to the maximum likelihood estimator but the computation time is much less. In cooperative localization, a blindfolded node uses information from not only anchors but also other blindfolded nodes. After being compared with the distributed maximum likelihood estimator and the distributed weighted-multidimensional scaling (dwMDS) method, it is recognized that the estimator performs well in accuracy, computation time, and the use of wireless transmissions under various wireless environments.