{"title":"使用子阵列数据的多信号定位","authors":"J. Sheinvald, M. Wax","doi":"10.1109/ICASSP.1995.478492","DOIUrl":null,"url":null,"abstract":"A new technique for localisation of multiple signals is presented. Unlike existing techniques which require that the whole array be sampled simultaneously and consequently require many receivers, our technique allows us to sample arbitrary subarrays sequentially and consequently significantly reduces the required number of receivers. The estimation method we use in conjunction with this sampling scheme is based on approximating the corresponding maximum likelihood estimator by a computationally simpler generalized least squares (GLS) estimator that is proved to be both consistent and efficient.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Localization of multiple signals using subarrays data\",\"authors\":\"J. Sheinvald, M. Wax\",\"doi\":\"10.1109/ICASSP.1995.478492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new technique for localisation of multiple signals is presented. Unlike existing techniques which require that the whole array be sampled simultaneously and consequently require many receivers, our technique allows us to sample arbitrary subarrays sequentially and consequently significantly reduces the required number of receivers. The estimation method we use in conjunction with this sampling scheme is based on approximating the corresponding maximum likelihood estimator by a computationally simpler generalized least squares (GLS) estimator that is proved to be both consistent and efficient.\",\"PeriodicalId\":300119,\"journal\":{\"name\":\"1995 International Conference on Acoustics, Speech, and Signal Processing\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1995 International Conference on Acoustics, Speech, and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.1995.478492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1995 International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1995.478492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Localization of multiple signals using subarrays data
A new technique for localisation of multiple signals is presented. Unlike existing techniques which require that the whole array be sampled simultaneously and consequently require many receivers, our technique allows us to sample arbitrary subarrays sequentially and consequently significantly reduces the required number of receivers. The estimation method we use in conjunction with this sampling scheme is based on approximating the corresponding maximum likelihood estimator by a computationally simpler generalized least squares (GLS) estimator that is proved to be both consistent and efficient.