Efficient estimation of the parameters in a sum of complex sinusoids in complex autoregressive noise

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    Although the periodogram maximizer has good asymptotic properties in the case of a single sinusoid in colored noise, in low SNR conditions and/or in the case of small sample size, the data need to be prewhitened in order for the periodogram maximizer be likely to occur near the true frequency. In this paper we derive an efficient least squares algorithm for estimating the frequencies, amplitudes, phases and autoregressive parameters for a sum of sinusoids in complex autoregressive noise. The procedure is seen to be a generalization of the Levinson-Durbin algorithm, an efficient technique for estimating the parameters in an autoregression.

    Original languageEnglish
    Title of host publicationConference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC
    EditorsMichael B. Matthews
    Place of PublicationPiscataway, NJ
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Number of pages5
    ISBN (Print)9781424421107
    Publication statusPublished - 2007
    Event41st Asilomar Conference on Signals, Systems and Computers, ACSSC - Pacific Grove, CA, United States
    Duration: 4 Nov 20077 Nov 2007


    Other41st Asilomar Conference on Signals, Systems and Computers, ACSSC
    Country/TerritoryUnited States
    CityPacific Grove, CA

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