Adaptive techniques in compressed sensing based direction of arrival estimation

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buir.advisorArıkan, Orhan
dc.contributor.authorKılıç, Berkan
dc.date.accessioned2021-08-04T05:55:58Z
dc.date.available2021-08-04T05:55:58Z
dc.date.copyright2021-07
dc.date.issued2021-07
dc.date.submitted2021-07-13
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Master's): Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2021.en_US
dc.descriptionIncludes bibliographical references (leaves 109-120).en_US
dc.description.abstractDirection of arrival (DOA) estimation is an important research area having exten-sive applications including radar, sonar, wireless communications, and electronic warfare systems. Development and popularization of the compressed sensing (CS) theory has led to a vast literature on the use of the CS techniques in DOA esti-mation which has been shown to be superior over the classical techniques under various scenarios. In the CS based techniques, measurement matrices determine the received information while sparsity promoting reconstruction algorithms are used to estimate the unknown DOAs. Hence, design of measurement matrices and sparse reconstruction algorithms are among the most important aspects of the CS theory. In this thesis, both aspects are investigated and novel techniques are proposed for improved performance. Following a brief explanation of the classical and the CS based DOA estimation techniques, a new optimization perspective is introduced on the Capon’s beam-former by using the minimum mean square error criterion. After that, a mea-surement matrix design methodology exploiting prior information on the source environment is introduced. Hardware and sofware implementation constraints of the introduced method are investigated and more efficient alternatives are pro-posed. Additionally, an adaptive dictionary design algorithm is introduced for more effective use of the prior information. Lastly, the Cramer-Rao Lower Bound expression for the compressed DOA signal models is derived and its implications on the measurement matrix design are investigated leading to a sector based mea-surement matrix design technique along with a novel reconstruction algorithm.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityby Berkan Kılıçen_US
dc.embargo.release2022-01-07
dc.format.extentxvi, 137 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB154489
dc.identifier.urihttp://hdl.handle.net/11693/76404
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCompressed sensingen_US
dc.subjectDirection of arrival estimationen_US
dc.subjectMeasurement matrix designen_US
dc.subjectSparse reconstructionen_US
dc.titleAdaptive techniques in compressed sensing based direction of arrival estimationen_US
dc.title.alternativeSıkıştırılmış algılama tabanlı geliş açısı kestiriminde uyarlanabilir teknikleren_US
dc.typeThesisen_US

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