{"title":"COMPRESSED SENSING DOA ESTIMATION IN THE PRESENCE OF UNKNOWN NOISE","authors":"A. A. Salama, M. Ahmad, M. Swamy","doi":"10.2528/pierc20031204","DOIUrl":null,"url":null,"abstract":"A new compressive sensing-based direction of arrival (DOA) estimation technique for source signal detection in the presence of unknown noise, based on the generalized correlation decomposition (GCD) algorithm, is presented. The proposed algorithm does not depend on the singular value decomposition nor on the orthogonality of the signal and the noise subspaces. Hence, the DOA estimation can be done without an a priori knowledge of the number of sources. The proposed algorithm can estimate more sources than the number of physical sensors used without any constraints or assumptions about the nature of the signal sources. It can estimate coherent source signals as well as closely-spaced sources using a small number of snapshots.","PeriodicalId":54551,"journal":{"name":"Progress in Electromagnetics Research-Pier","volume":"112 1","pages":"47-62"},"PeriodicalIF":6.7000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Progress in Electromagnetics Research-Pier","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.2528/pierc20031204","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Physics and Astronomy","Score":null,"Total":0}
引用次数: 3
Abstract
A new compressive sensing-based direction of arrival (DOA) estimation technique for source signal detection in the presence of unknown noise, based on the generalized correlation decomposition (GCD) algorithm, is presented. The proposed algorithm does not depend on the singular value decomposition nor on the orthogonality of the signal and the noise subspaces. Hence, the DOA estimation can be done without an a priori knowledge of the number of sources. The proposed algorithm can estimate more sources than the number of physical sensors used without any constraints or assumptions about the nature of the signal sources. It can estimate coherent source signals as well as closely-spaced sources using a small number of snapshots.
期刊介绍:
Progress In Electromagnetics Research (PIER) publishes peer-reviewed original and comprehensive articles on all aspects of electromagnetic theory and applications. This is an open access, on-line journal PIER (E-ISSN 1559-8985). It has been first published as a monograph series on Electromagnetic Waves (ISSN 1070-4698) in 1989. It is freely available to all readers via the Internet.