{"title":"A new adaptive algorithm of frequency-wavenumber estimation","authors":"L. Yin, L. Zhou","doi":"10.1109/APS.1988.94363","DOIUrl":null,"url":null,"abstract":"The authors present a novel high-resolution online method for two dimensional (2-D) harmonic retrieval. This method yields asymptotically unbiased estimates of both the DOAs (directions of arrival) and the frequencies of the impinging sources. This adaptive method is based on the singular value decomposition of the signal matrix formed by the maximum eigenvector of the 2-D covariance matrix of the received signal. Compared with other 2-D adaptive algorithms, this method is a more stable 2-D spectral technique. Its convergence rate is faster, and its computational requirement is smaller.<<ETX>>","PeriodicalId":211271,"journal":{"name":"1988 IEEE AP-S. International Symposium, Antennas and Propagation","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1988 IEEE AP-S. International Symposium, Antennas and Propagation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APS.1988.94363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The authors present a novel high-resolution online method for two dimensional (2-D) harmonic retrieval. This method yields asymptotically unbiased estimates of both the DOAs (directions of arrival) and the frequencies of the impinging sources. This adaptive method is based on the singular value decomposition of the signal matrix formed by the maximum eigenvector of the 2-D covariance matrix of the received signal. Compared with other 2-D adaptive algorithms, this method is a more stable 2-D spectral technique. Its convergence rate is faster, and its computational requirement is smaller.<>