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dc.contributor.authorVillares Piera, Nemesio J.
dc.contributor.authorVázquez Grau, Gregorio
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2008-02-04T10:48:32Z
dc.date.available2008-02-04T10:48:32Z
dc.date.created2004-06-11
dc.date.issued2005-07-31
dc.identifier.citationVillares Piera, J.; Vázquez Grau, G. Second-order parameter estimation. IEEE Transactions on Signal Processing, 2005, vol. 53, núm. 7, p. 2408-2420.
dc.identifier.issn1053-587X
dc.identifier.urihttp://hdl.handle.net/2117/1558
dc.description.abstractThis work provides a general framework for the design of second-order blind estimators without adopting any approximation about the observation statistics or the a priori distribution of the parameters. The proposed solution is obtained minimizing the estimator variance subject to some constraints on the estimator bias. The resulting optimal estimator is found to depend on the observation fourth-order moments that can be calculated analytically from the known signal model. Unfortunately, in most cases, the performance of this estimator is severely limited by the residual bias inherent to nonlinear estimation problems. To overcome this limitation, the second-order minimum variance unbiased estimator is deduced from the general solution by assuming accurate prior information on the vector of parameters. This small-error approximation is adopted to design iterative estimators or trackers. It is shown that the associated variance constitutes the lower bound for the variance of any unbiased estimator based on the sample covariance matrix. The paper formulation is then applied to track the angle-of-arrival (AoA) of multiple digitally-modulated sources by means of a uniform linear array. The optimal second-order tracker is compared with the classical maximum likelihood (ML) blind methods that are shown to be quadratic in the observed data as well. Simulations have confirmed that the discrete nature of the transmitted symbols can be exploited to improve considerably the discrimination of near sources in medium-to-high SNR scenarios.
dc.format.extent2408-2420
dc.language.isoeng
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal
dc.subject.lcshSignal processing
dc.subject.lcshNumerical analysis
dc.subject.lcshSimulation
dc.subject.otherA priori distribution
dc.subject.otherAngle-of-arrival estimation
dc.subject.otherBlind estimator
dc.subject.otherCovariance matrices
dc.subject.otherdirection-of-arrival estimation
dc.subject.otherIterative estimator
dc.subject.otherIterative methods
dc.subject.otherMaximum likelihood blind method
dc.subject.otherMaximum likelihood estimation
dc.subject.otherNonlinear estimation
dc.subject.otherSecond-order minimum variance unbiased estimator
dc.subject.otherSecond-order parameter estimation
dc.subject.otherSignal processing
dc.subject.otherSmall-error approximation
dc.subject.otherUniform linear array
dc.titleSecond-order parameter estimation
dc.typeArticle
dc.subject.lemacProcessament del senyal
dc.subject.lemacAnàlisi numèrica
dc.subject.lemacSimulació de sistemes
dc.contributor.groupUniversitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.relation.projectidcttTIC2003-05482
dc.relation.projectidcttTEC2004-04526
dc.relation.projectidctt2001-SGR-00268


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