{"title":"DOA matrix based robust beamforming in the presence of steering vector mismatch","authors":"Wei Guo, Pengcheng Mu, Jiancun Fan, Huiming Wang, Qinye Yin","doi":"10.1109/GlobalSIP.2014.7032289","DOIUrl":null,"url":null,"abstract":"The minimum variance distortionless response (MV-DR) beamformer is very sensitive to the steering vector mismatch. Such mismatch can lead to serious degradation of the beamforming performance especially at high signal-to-noise ratio (SNR). In this paper, a new robust beamformer based on the DOA matrix is proposed to solve the steering vector mismatch. Through the left eigendecomposition of the DOA matrix, a subspace which is orthogonal to the interference subspace can be obtained and is further used to construct the beamforming weight vector. Simulation results show the effectiveness of our proposed method.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2014.7032289","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 minimum variance distortionless response (MV-DR) beamformer is very sensitive to the steering vector mismatch. Such mismatch can lead to serious degradation of the beamforming performance especially at high signal-to-noise ratio (SNR). In this paper, a new robust beamformer based on the DOA matrix is proposed to solve the steering vector mismatch. Through the left eigendecomposition of the DOA matrix, a subspace which is orthogonal to the interference subspace can be obtained and is further used to construct the beamforming weight vector. Simulation results show the effectiveness of our proposed method.