Highly Robust Complex Covariance Estimators With Applications to Sensor Array Processing

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dc.contributor.authorFishbone, Justin A.en
dc.contributor.authorMili, Lamine M.en
dc.date.accessioned2024-01-24T14:27:49Zen
dc.date.available2024-01-24T14:27:49Zen
dc.date.issued2023-03-24en
dc.description.abstractMany applications in signal processing require the estimation of mean and covariance matrices of multivariate complex-valued data. Often, the data are non-Gaussian and are corrupted by outliers or impulsive noise. To mitigate this, robust estimators are employed. However, existing robust estimation techniques employed in signal processing, such as M-estimators, provide limited robustness in the multivariate case. For this reason, this paper introduces the signal processing community to the highly robust class of multivariate estimators called multivariate S-estimators. The paper extends multivariate S-estimation theory to the complex-valued domain. The theoretical performances of S-estimators are explored and compared with M-estimators through the practical lens of the minimum variance distortionless response (MVDR) beamformer, and the empirical finite-sample performances of the estimators are explored through the practical lens of direction-of-arrival (DOA) estimation using the multiple signal classification (MUSIC) algorithm.en
dc.description.versionPublished versionen
dc.format.extentPages 208-224en
dc.format.extent17 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1109/OJSP.2023.3261806en
dc.identifier.eissn2644-1322en
dc.identifier.issn2644-1322en
dc.identifier.orcidMili, Lamine [0000-0001-6134-3945]en
dc.identifier.urihttps://hdl.handle.net/10919/117645en
dc.identifier.volume4en
dc.language.isoenen
dc.publisherIEEEen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectSignal processingen
dc.subjectEstimationen
dc.subjectCovariance matricesen
dc.subjectRobustnessen
dc.subjectProbability density functionen
dc.subjectElectric breakdownen
dc.subjectSymmetric matricesen
dc.subjectComplex elliptically symmetric distributionen
dc.subjectcomplex-valued S-estimatoren
dc.subjectcovariance and shape matrix estimationen
dc.subjectrobust estimation of multivariate location and scatteren
dc.subjectSq-estimatoren
dc.titleHighly Robust Complex Covariance Estimators With Applications to Sensor Array Processingen
dc.title.serialIEEE Open Journal of Signal Processingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dc.type.otherJournalen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Electrical and Computer Engineeringen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen

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