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dc.contributor.authorAli, Hussain
dc.contributor.authorBallal, Tarig
dc.contributor.authorAl-Naffouri, Tareq Y.
dc.contributor.authorSharawi, Mohammad S.
dc.date.accessioned2021-02-24T06:40:11Z
dc.date.available2021-02-24T06:40:11Z
dc.date.issued2021-01-18
dc.identifier.citationAli, H., Ballal, T., Al-Naffouri, T. Y., & Sharawi, M. S. (2020). DOA Estimation with a Rank-deficient Covariance matrix: A Regularized Least-squares approach. 2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium). doi:10.23919/usnc/ursi49741.2020.9321628
dc.identifier.isbn978-1-7281-6197-6
dc.identifier.doi10.23919/USNC/URSI49741.2020.9321628
dc.identifier.urihttp://hdl.handle.net/10754/667633
dc.description.abstractDOA estimation in the presence of coherent sources using a small number of snapshots faces the challenge of rank deficiency of the received signal covariance matrix. When the covariance matrix is rank deficient, only the pseudo inverse of the covariance matrix can be computed, which can give undesirable results. Traditionally, regularized least-squares (RLS) algorithms are used to tackle estimation problems in systems with ill-conditioned or rank deficient matrices. In this work, we combine the Capon beamformer with the RLS framework to develop a DOA estimation method for scenarios with rank deficient covariance matrices. Simulation results demonstrate the effectiveness of the proposed approach.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/9321628/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9321628
dc.rightsArchived with thanks to IEEE
dc.subjectDOA
dc.subjectregularized least-squares
dc.subjectcoherent sources
dc.subjectrank-deficient matrices
dc.titleDOA Estimation with a Rank-deficient Covariance matrix: A Regularized Least-squares approach
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.conference.date5-10 July 2020
dc.conference.name2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium)
dc.conference.locationMontreal, QC, Canada
dc.eprint.versionPost-print
dc.contributor.institutionNational University of Sciences and Technology (NUST),College of Signals,Department of Electrical Engineering,Islamabad,Pakistan
dc.contributor.institutionPolytechnique Montréal,Poly-Grames Research Center,Electrical Engineering Department,Montreal,QC,Canada,H3T 1J4
dc.identifier.pages87-88
kaust.personBallal, Tarig
kaust.personAl-Naffouri, Tareq Y.
dc.date.accepted2020
dc.identifier.eid2-s2.0-85100611647


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