Adaptive measurement matrix design in compressed sensing based direction of arrival estimation

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buir.contributor.authorKılıç, Berkan
buir.contributor.authorGüngör, Alper
buir.contributor.authorKalfa, Mert
buir.contributor.authorArıkan, Orhan
buir.contributor.orcidKılıç, Berkan|0000-0003-0367-4329
buir.contributor.orcidGüngör, Alper|0000-0002-3043-9124
buir.contributor.orcidKalfa, Mert|0000-0002-6462-1776
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
dc.citation.epage1885en_US
dc.citation.spage1881en_US
dc.contributor.authorKılıç, Berkan
dc.contributor.authorGüngör, Alper
dc.contributor.authorKalfa, Mert
dc.contributor.authorArıkan, Orhan
dc.coverage.spatialAmsterdam, Netherlands
dc.date.accessioned2022-03-11T12:33:35Z
dc.date.available2022-03-11T12:33:35Z
dc.date.issued2021
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionConference Name: 28th European Signal Processing Conference (EUSIPCO 2020) IEEEen_US
dc.descriptionConference Date: 18-21 Jan. 2021en_US
dc.description.abstractDesign of measurement matrices is an important aspect of compressed sensing (CS) based direction of arrival (DoA) applications that enables reduction in the analog channels to be processed in sparse target environments. Here, a novel measurement matrix design methodology for CS based DoA estimation is proposed and its superior performance over alternative measurement matrix design methodologies is demonstrated. The proposed method uses prior probability distribution of the targets to improve performance. Compared to the state-of-the-art techniques, it is quantitatively demonstrated that the proposed measurement matrix design approach enables significant reduction in the number of analog channels to be processed and adapts to a priori information on the target scene.en_US
dc.description.provenanceSubmitted by Evrim Ergin (eergin@bilkent.edu.tr) on 2022-03-11T12:33:35Z No. of bitstreams: 1 Adaptive_measurement_matrix_design_in_compressed_sensing_based_direction_of_arrival_estimation.pdf: 804456 bytes, checksum: 21712c5f243bbdf121744852398f555e (MD5)en
dc.description.provenanceMade available in DSpace on 2022-03-11T12:33:35Z (GMT). No. of bitstreams: 1 Adaptive_measurement_matrix_design_in_compressed_sensing_based_direction_of_arrival_estimation.pdf: 804456 bytes, checksum: 21712c5f243bbdf121744852398f555e (MD5) Previous issue date: 2021en
dc.identifier.doi10.23919/Eusipco47968.2020.9287679en_US
dc.identifier.eisbn978-9-0827-9705-3
dc.identifier.isbn978-1-7281-5001-7
dc.identifier.urihttp://hdl.handle.net/11693/77728
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://doi.org/10.23919/Eusipco47968.2020.9287679en_US
dc.source.title2020 28th European Signal Processing Conference (EUSIPCO)en_US
dc.subjectDirection of arrival estimationen_US
dc.subjectCompressed sensingen_US
dc.subjectMeasurement matrix designen_US
dc.titleAdaptive measurement matrix design in compressed sensing based direction of arrival estimationen_US
dc.typeProceedings Paperen_US

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