{"title":"基于均匀圆形阵列的复杂室内环境近场源定位","authors":"Xiansheng Guo, Baocang Li, L. Chu, Disong Wang","doi":"10.1109/ChinaSIP.2014.6889275","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a covariance matrix matching technique using a uniform circular array (UCA) to localize a near-field source in indoor multi-path environment. Firstly, we exploit off-line measured covariance matrices for suitable spaced reference points and storing these matrices as a fingerprint; Secondly, a matrix matching algorithm is designed to obtain the position of source. Compared with received signal strength (RSS) fingerprint, covariance matrix can offer more channel information of indoor environment, hence, our proposed algorithm outperforms RSS based algorithm in accuracy of localization. Finally, some simulation results show the efficacy of our proposed technique.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Near-field source localization in complex indoor environment using uniform circular array\",\"authors\":\"Xiansheng Guo, Baocang Li, L. Chu, Disong Wang\",\"doi\":\"10.1109/ChinaSIP.2014.6889275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a covariance matrix matching technique using a uniform circular array (UCA) to localize a near-field source in indoor multi-path environment. Firstly, we exploit off-line measured covariance matrices for suitable spaced reference points and storing these matrices as a fingerprint; Secondly, a matrix matching algorithm is designed to obtain the position of source. Compared with received signal strength (RSS) fingerprint, covariance matrix can offer more channel information of indoor environment, hence, our proposed algorithm outperforms RSS based algorithm in accuracy of localization. Finally, some simulation results show the efficacy of our proposed technique.\",\"PeriodicalId\":248977,\"journal\":{\"name\":\"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ChinaSIP.2014.6889275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ChinaSIP.2014.6889275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Near-field source localization in complex indoor environment using uniform circular array
In this paper, we propose a covariance matrix matching technique using a uniform circular array (UCA) to localize a near-field source in indoor multi-path environment. Firstly, we exploit off-line measured covariance matrices for suitable spaced reference points and storing these matrices as a fingerprint; Secondly, a matrix matching algorithm is designed to obtain the position of source. Compared with received signal strength (RSS) fingerprint, covariance matrix can offer more channel information of indoor environment, hence, our proposed algorithm outperforms RSS based algorithm in accuracy of localization. Finally, some simulation results show the efficacy of our proposed technique.