Please use this identifier to cite or link to this item: https://doi.org/10.4218/etrij.11.0110.0138
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dc.titleImproved single-tone frequency estimation by averaging and weighted linear prediction
dc.contributor.authorSo, H.C.
dc.contributor.authorLiu, H.
dc.date.accessioned2014-12-12T07:49:27Z
dc.date.available2014-12-12T07:49:27Z
dc.date.issued2011-02
dc.identifier.citationSo, H.C., Liu, H. (2011-02). Improved single-tone frequency estimation by averaging and weighted linear prediction. ETRI Journal 33 (1) : 27-31. ScholarBank@NUS Repository. https://doi.org/10.4218/etrij.11.0110.0138
dc.identifier.issn12256463
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/116402
dc.description.abstractThis paper addresses estimating the frequency of a cisoid in the presence of white Gaussian noise, which has numerous applications in communications, radar, sonar, and instrumentation and measurement. Due to the nonlinear nature of the frequency estimation problem, there is threshold effect, that is, large error estimates or outliers will occur at sufficiently low signal-to-noise ratio (SNR) conditions. Utilizing the ideas of averaging to increase SNR and weighted linear prediction, an optimal frequency estimator with smaller threshold SNR is developed. Computer simulations are included to compare its mean square error performance with that of the maximum likelihood (ML) estimator, improved weighted phase averager, generalized weighted linear predictor, and single weighted sample correlator as well as Cramér-Rao lower bound. In particular, with smaller computational requirement, the proposed estimator can achieve the same threshold and estimation performance of the ML method. © 2011 ETRI.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.4218/etrij.11.0110.0138
dc.sourceScopus
dc.subjectFrequency estimation
dc.subjectLinear prediction
dc.subjectThreshold performance
dc.typeArticle
dc.contributor.departmentTROPICAL MARINE SCIENCE INSTITUTE
dc.description.doi10.4218/etrij.11.0110.0138
dc.description.sourcetitleETRI Journal
dc.description.volume33
dc.description.issue1
dc.description.page27-31
dc.description.codenETJOF
dc.identifier.isiut000287278200005
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