{"title":"New approach for finding DOA in array antennas using cyclostationarity","authors":"H. Tsuji, J. Xin, S. Yoshimoto, A. Sano","doi":"10.1109/WCC.1997.622250","DOIUrl":null,"url":null,"abstract":"A new approach is presented for estimating the directions of arrival (DOA) of desired signals in array antennas using cyclostationarity. The new algorithm can correctly estimate the DOA of desired signals by suppressing undesired signals. We apply the outputs of antenna sensors to the linear prediction model and calculate the cyclic correlation to utilize the cyclostationarity of the desired signals. We also evaluate the error of the estimate of the cyclic correlation function in the linear prediction model and correctly estimate the DOA of the desired signals. Furthermore, we take advantage of the signal selective DOA estimation to give the scheme of an adaptive beamforming. We compare our results with the results of conventional approaches in the presence of interference and at low signal to noise ratios (SNR). Numerical examples are presented to show the effectiveness of the proposed method.","PeriodicalId":439434,"journal":{"name":"Proceedings of 1997 Wireless Communications Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1997 Wireless Communications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCC.1997.622250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A new approach is presented for estimating the directions of arrival (DOA) of desired signals in array antennas using cyclostationarity. The new algorithm can correctly estimate the DOA of desired signals by suppressing undesired signals. We apply the outputs of antenna sensors to the linear prediction model and calculate the cyclic correlation to utilize the cyclostationarity of the desired signals. We also evaluate the error of the estimate of the cyclic correlation function in the linear prediction model and correctly estimate the DOA of the desired signals. Furthermore, we take advantage of the signal selective DOA estimation to give the scheme of an adaptive beamforming. We compare our results with the results of conventional approaches in the presence of interference and at low signal to noise ratios (SNR). Numerical examples are presented to show the effectiveness of the proposed method.