{"title":"信号特征向量分解及到达方向估计","authors":"Qing-Guang Liu, L. Zou","doi":"10.1109/CICCAS.1991.184356","DOIUrl":null,"url":null,"abstract":"Presents a new algorithm for direction-of-arrival (DOA) estimation. Based on the unique decomposition of large eigenvectors of array covariance matrix, an iterative algorithm is proposed, which is valid in any case whether the sources are coherent or not. Simulations showed that the new approach has a significant improvement in performance over MUSIC at low SNR or short data.<<ETX>>","PeriodicalId":119051,"journal":{"name":"China., 1991 International Conference on Circuits and Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Signal eigenvectors decomposition and direction of arrival estimation\",\"authors\":\"Qing-Guang Liu, L. Zou\",\"doi\":\"10.1109/CICCAS.1991.184356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Presents a new algorithm for direction-of-arrival (DOA) estimation. Based on the unique decomposition of large eigenvectors of array covariance matrix, an iterative algorithm is proposed, which is valid in any case whether the sources are coherent or not. Simulations showed that the new approach has a significant improvement in performance over MUSIC at low SNR or short data.<<ETX>>\",\"PeriodicalId\":119051,\"journal\":{\"name\":\"China., 1991 International Conference on Circuits and Systems\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"China., 1991 International Conference on Circuits and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICCAS.1991.184356\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"China., 1991 International Conference on Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICCAS.1991.184356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Signal eigenvectors decomposition and direction of arrival estimation
Presents a new algorithm for direction-of-arrival (DOA) estimation. Based on the unique decomposition of large eigenvectors of array covariance matrix, an iterative algorithm is proposed, which is valid in any case whether the sources are coherent or not. Simulations showed that the new approach has a significant improvement in performance over MUSIC at low SNR or short data.<>
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
