{"title":"Robust adaptive beamforming with positive semi-definite constraint using single variable minimization","authors":"Suraj Patil, V. Nagrale","doi":"10.1109/IIC.2015.7151003","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new method to solve the robust adaptive beamforming problem for the general rank signal model with positive semi-definite constraint. On applying the worst-case performance optimization approach, the considered robust adaptive beamforming problem generates a non-convex optimization problem. Here, we propose a two step closed form solution of the formulated problem, wherein a new single variable minimization problem is constructed. Result of this minimization is used to solve the robust adaptive beamforming problem. Simulation results verify the improvement in the performance by the proposed method over the current robust adaptive beamforming methods for general-rank signal model.","PeriodicalId":155838,"journal":{"name":"2015 International Conference on Industrial Instrumentation and Control (ICIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Industrial Instrumentation and Control (ICIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIC.2015.7151003","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
In this paper, we propose a new method to solve the robust adaptive beamforming problem for the general rank signal model with positive semi-definite constraint. On applying the worst-case performance optimization approach, the considered robust adaptive beamforming problem generates a non-convex optimization problem. Here, we propose a two step closed form solution of the formulated problem, wherein a new single variable minimization problem is constructed. Result of this minimization is used to solve the robust adaptive beamforming problem. Simulation results verify the improvement in the performance by the proposed method over the current robust adaptive beamforming methods for general-rank signal model.