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On the Deterministic CRB for DOA Estimation in Unknown Noise Fields Using Sparse Sensor Arrays

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dc.contributor.authorKleinsteuber, M
dc.contributor.authorSeghouane, Abd-Krim
dc.date.accessioned2015-12-10T22:15:04Z
dc.date.issued2008
dc.date.updated2015-12-09T08:12:51Z
dc.description.abstractThe Cramé-Rao bound (CRB) plays an important role in direction of arrival (DOA) estimation because it is always used as a benchmark for comparison of the different proposed estimation algorithms. In this correspondence, using well-known techniques of glo
dc.identifier.issn1053-587X
dc.identifier.urihttp://hdl.handle.net/1885/50463
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.sourceIEEE Transactions on Signal Processing
dc.subjectKeywords: Computational geometry; Cramer-Rao bounds; Maximum likelihood estimation; Sensor arrays; Differential geometry; Global analysis; Direction of arrival Cramér-Rao bound (CRB); Differential geometry; Direction of arrival (DOA) estimation; Maximum likelihood
dc.titleOn the Deterministic CRB for DOA Estimation in Unknown Noise Fields Using Sparse Sensor Arrays
dc.typeJournal article
local.bibliographicCitation.issue2
local.bibliographicCitation.lastpage864
local.bibliographicCitation.startpage860
local.contributor.affiliationKleinsteuber, M, University of Wurzburg
local.contributor.affiliationSeghouane, Abd-Krim, College of Engineering and Computer Science, ANU
local.contributor.authoruidSeghouane, Abd-Krim, u4593707
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor090609 - Signal Processing
local.identifier.absfor010405 - Statistical Theory
local.identifier.ariespublicationu4334215xPUB204
local.identifier.citationvolume56
local.identifier.doi10.1109/TSP.2007.907832
local.identifier.scopusID2-s2.0-39649107334
local.type.statusPublished Version

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