Statistics of the MLE and Approximate Upper and Lower Bounds-Part 1: Application to TOA Estimation

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buir.contributor.authorGezici, Sinan
dc.citation.epage5676en_US
dc.citation.issueNumber21en_US
dc.citation.spage5663en_US
dc.citation.volumeNumber62en_US
dc.contributor.authorMallat, A.en_US
dc.contributor.authorGezici, Sinanen_US
dc.contributor.authorDardari, D.en_US
dc.contributor.authorCraeye, C.en_US
dc.contributor.authorVandendorpe, L.en_US
dc.date.accessioned2015-07-28T12:02:49Z
dc.date.available2015-07-28T12:02:49Z
dc.date.issued2014-08en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractIn nonlinear deterministic parameter estimation, the maximum likelihood estimator (MLE) is unable to attain the Cramer-Rao lower bound at low and medium signal-to-noise ratios (SNR) due the threshold and ambiguity phenomena. In order to evaluate the achieved mean-squared-error (MSE) at those SNR levels, we propose new MSE approximations (MSEA) and an approximate upper bound by using the method of interva l estimation (MIE). The mean and the distribution of the MLE ar e approximated as well. The MIE consists in splitting the a priori domain of the unknown parameter into intervals and computin g the statistics of the estimator in each interval. Also, we derive an approximate lower bound (ALB) based on the Taylor series expansion of noise and an ALB family by employing the binary detection principle. The accurateness of the proposed MSEAs and the tightness of the derived approximate bounds 1 are validated by considering the example of time-of-arrival estimation.en_US
dc.description.provenanceMade available in DSpace on 2015-07-28T12:02:49Z (GMT). No. of bitstreams: 1 8347.pdf: 628702 bytes, checksum: b34a44cea0cc2d5ab46d7ebd581d2e7c (MD5)en
dc.identifier.doi10.1109/TSP.2003.814469en_US
dc.identifier.issn1053-587X
dc.identifier.urihttp://hdl.handle.net/11693/12741
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/TSP.2003.814469en_US
dc.source.titleIEEE Trans on Signal Processingen_US
dc.subjectNonlinear Estimationen_US
dc.subjectThreshold And Ambiguity Phenomenaen_US
dc.subjectMaximum Likelihood Estimatoren_US
dc.subjectMean-squared-erroren_US
dc.subjectUpper And Lowers Boundsen_US
dc.subjectTime-of-arrivalen_US
dc.titleStatistics of the MLE and Approximate Upper and Lower Bounds-Part 1: Application to TOA Estimationen_US
dc.typeArticleen_US

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