Improved Parameter Estimation Schemes for Damped Sinusoidal Signals Based on Low-Rank Hankel Approximation

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dc.contributor.authorLi, Yeen_US
dc.contributor.authorLiu, K.J. Rayen_US
dc.contributor.authorRazavilar, J.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:58:32Z
dc.date.available2007-05-23T09:58:32Z
dc.date.issued1995en_US
dc.description.abstractThe parameter estimation of damped sinusoidal signals is an important issue in spectral analysis and many applications. The existing algorithms, such as the KT algorithms [8] and the TLS algorithms [13], are based on the low-rank approximation of prediction matrix, which ignores the Hankel property of the prediction matrix. We will prove in this paper that the performance of parameter estimation can be improved if both rank- deficient and Hankel properties of the prediction matrix are exploited in the matrix approximation. Based on this idea, a modified KT (MKT) algorithm and a super resolution algorithm- damped MUSIC (DMUSIC) algorithm are proposed. Computer simulation results demonstrate that, compared with the original KT algorithm, the MKT and MUSIC algorithms have about 5dB lower noise threshold and can estimate the parameters of signal with larger damping factors.en_US
dc.format.extent745598 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5606
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1995-11en_US
dc.subjectestimationen_US
dc.subjectsignal processingen_US
dc.subjectSystems Integration Methodologyen_US
dc.titleImproved Parameter Estimation Schemes for Damped Sinusoidal Signals Based on Low-Rank Hankel Approximationen_US
dc.typeTechnical Reporten_US

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