{"title":"联合稀疏重建方法的DOA估计和阵列配准","authors":"Thomas Wiese, L. Weiland, W. Utschick","doi":"10.1109/SPAWC.2015.7227088","DOIUrl":null,"url":null,"abstract":"Two uniform linear arrays with inexactly known relative positions shall be used for coherent direction of arrival estimation. We show that in the narrowband case the estimation of the displacement parameter is well posed if the number of sources is known. Furthermore, we propose a fast registration method that estimates the unknown displacement parameter using a combination of sparse reconstruction algorithms for distributed compressed sensing and Newton's method.","PeriodicalId":211324,"journal":{"name":"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"DOA estimation and array registration with joint sparse reconstruction methods\",\"authors\":\"Thomas Wiese, L. Weiland, W. Utschick\",\"doi\":\"10.1109/SPAWC.2015.7227088\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two uniform linear arrays with inexactly known relative positions shall be used for coherent direction of arrival estimation. We show that in the narrowband case the estimation of the displacement parameter is well posed if the number of sources is known. Furthermore, we propose a fast registration method that estimates the unknown displacement parameter using a combination of sparse reconstruction algorithms for distributed compressed sensing and Newton's method.\",\"PeriodicalId\":211324,\"journal\":{\"name\":\"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAWC.2015.7227088\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAWC.2015.7227088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DOA estimation and array registration with joint sparse reconstruction methods
Two uniform linear arrays with inexactly known relative positions shall be used for coherent direction of arrival estimation. We show that in the narrowband case the estimation of the displacement parameter is well posed if the number of sources is known. Furthermore, we propose a fast registration method that estimates the unknown displacement parameter using a combination of sparse reconstruction algorithms for distributed compressed sensing and Newton's method.