{"title":"鲁棒自适应波束空间预处理新成果","authors":"A. Hassanien, S.A. Vorobyovy","doi":"10.1109/SAM.2008.4606880","DOIUrl":null,"url":null,"abstract":"In this paper, we develop an algorithm for data-adaptive beamspace preprocessing with robustness against out-of-sector sources. Our algorithm yields an orthogonal beamspace matrix and, hence, it preserves the white noise property at the output of the beamspace preprocessor. The beamspace matrix is designed as a matrix filter that maintains an almost distortionless response towards sources within the beamspace sector while maximally rejects all out-of-sector sources. The columns of the beamspace matrix are designed sequentially, one column at a time. This sequential implementation is curried out by imposing orthogonality constraints between beamspace matrix columns. The proposed algorithm is computationally less expensive as compared to the existing data-adaptive beamspace design techniques. Simulation results are provided to validate the robustness of the developed algorithm, and show its effectiveness.","PeriodicalId":422747,"journal":{"name":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"New results on robust adaptive beamspace preprocessing\",\"authors\":\"A. Hassanien, S.A. Vorobyovy\",\"doi\":\"10.1109/SAM.2008.4606880\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we develop an algorithm for data-adaptive beamspace preprocessing with robustness against out-of-sector sources. Our algorithm yields an orthogonal beamspace matrix and, hence, it preserves the white noise property at the output of the beamspace preprocessor. The beamspace matrix is designed as a matrix filter that maintains an almost distortionless response towards sources within the beamspace sector while maximally rejects all out-of-sector sources. The columns of the beamspace matrix are designed sequentially, one column at a time. This sequential implementation is curried out by imposing orthogonality constraints between beamspace matrix columns. The proposed algorithm is computationally less expensive as compared to the existing data-adaptive beamspace design techniques. Simulation results are provided to validate the robustness of the developed algorithm, and show its effectiveness.\",\"PeriodicalId\":422747,\"journal\":{\"name\":\"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAM.2008.4606880\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM.2008.4606880","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
New results on robust adaptive beamspace preprocessing
In this paper, we develop an algorithm for data-adaptive beamspace preprocessing with robustness against out-of-sector sources. Our algorithm yields an orthogonal beamspace matrix and, hence, it preserves the white noise property at the output of the beamspace preprocessor. The beamspace matrix is designed as a matrix filter that maintains an almost distortionless response towards sources within the beamspace sector while maximally rejects all out-of-sector sources. The columns of the beamspace matrix are designed sequentially, one column at a time. This sequential implementation is curried out by imposing orthogonality constraints between beamspace matrix columns. The proposed algorithm is computationally less expensive as compared to the existing data-adaptive beamspace design techniques. Simulation results are provided to validate the robustness of the developed algorithm, and show its effectiveness.