Underdetermined High-Resolution DOA Estimation: A 2 rho th-Order Source-Signal/Noise Subspace Constrained Optimization

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dc.contributor.authorChoi, Jin Hoko
dc.contributor.authorYoo, Chang-Dongko
dc.date.accessioned2015-04-15T02:01:01Z-
dc.date.available2015-04-15T02:01:01Z-
dc.date.created2015-02-11-
dc.date.created2015-02-11-
dc.date.created2015-02-11-
dc.date.issued2015-04-
dc.identifier.citationIEEE TRANSACTIONS ON SIGNAL PROCESSING, v.63, no.7, pp.1858 - 1873-
dc.identifier.issn1053-587X-
dc.identifier.urihttp://hdl.handle.net/10203/196057-
dc.description.abstractFor estimating the direction of arrival (DOA) s of non-stationary source signals such as speech and audio, a constrained optimization problem (COP) that exploits the spatial diversity provided by an array of sensors is formulated in terms of a noise-eliminated local 2 rho th-order cumulant matrix. The COP solution provides a weight vector to the look direction such that it is constrained to the 2 rho th-order source-signal subspace when the look direction is in alignment with the true DOA; otherwise, it is constrained to the 2 rho th-order noise subspace. This weight vector is incorporated into the spatial spectrum to determine the degree of orthogonality between itself and either the 2 rho th-order source-signal subspace when the number of sources is unknown, or the 2 rho th-order noise subspace when the number of sources is known. For a uniform linear array (ULA) of M sensors, the spatial spectrum for known number of sources can theoretically be shown to identify up to 2 rho(M - 1) sources. Realizing the difficulty in identifying stationarity in the received sensor signals, the estimate of the noise-eliminated local 2 rho th-order cumulant matrix is marginalized over various possible stationary segmentations, for a more robust DOA estimation. In this paper, we focus on the use of local second and fourth order cumulants (rho = 1, 2), and the proposed algorithms when rho = 1 outperformed the KR subspace-based algorithms and also the 4-MUSIC for globally non-stationary, non-Gaussian synthetic data and also for speech/audio in various adverse environments. We verified that the identifiability for rho = 2 is improved by two-folds compared to that for rho = 1 with an ULA.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.subjectHIGHER-ORDER STATISTICS-
dc.subjectVIRTUAL ARRAY CONCEPT-
dc.subjectSOURCE LOCALIZATION-
dc.subjectWIDE-BAND-
dc.subjectSIGNALS-
dc.subjectMUSIC-
dc.subjectARRIVAL-
dc.subjectNUMBER-
dc.titleUnderdetermined High-Resolution DOA Estimation: A 2 rho th-Order Source-Signal/Noise Subspace Constrained Optimization-
dc.typeArticle-
dc.identifier.wosid000350880900019-
dc.identifier.scopusid2-s2.0-84924678330-
dc.type.rimsART-
dc.citation.volume63-
dc.citation.issue7-
dc.citation.beginningpage1858-
dc.citation.endingpage1873-
dc.citation.publicationnameIEEE TRANSACTIONS ON SIGNAL PROCESSING-
dc.identifier.doi10.1109/TSP.2015.2401531-
dc.contributor.localauthorYoo, Chang-Dong-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorDOA estimation-
dc.subject.keywordAuthornon-stationary source signal-
dc.subject.keywordAuthorconstrained optimization-
dc.subject.keywordAuthorspatial spectrum-
dc.subject.keywordAuthorDOA estimation-
dc.subject.keywordAuthornon-stationary source signal-
dc.subject.keywordAuthorconstrained optimization-
dc.subject.keywordAuthorspatial spectrum-
dc.subject.keywordPlusHIGHER-ORDER STATISTICS-
dc.subject.keywordPlusVIRTUAL ARRAY CONCEPT-
dc.subject.keywordPlusSOURCE LOCALIZATION-
dc.subject.keywordPlusWIDE-BAND-
dc.subject.keywordPlusSIGNALS-
dc.subject.keywordPlusMUSIC-
dc.subject.keywordPlusARRIVAL-
dc.subject.keywordPlusNUMBER-
dc.subject.keywordPlusHIGHER-ORDER STATISTICS-
dc.subject.keywordPlusVIRTUAL ARRAY CONCEPT-
dc.subject.keywordPlusSOURCE LOCALIZATION-
dc.subject.keywordPlusWIDE-BAND-
dc.subject.keywordPlusSIGNALS-
dc.subject.keywordPlusMUSIC-
dc.subject.keywordPlusARRIVAL-
dc.subject.keywordPlusNUMBER-
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