• DocumentCode
    870531
  • Title

    Harmonic retrieval using higher order statistics: a deterministic formulation

  • Author

    Anderson, John M M ; Giannakis, Georgios B. ; Swami, Ananthram

  • Author_Institution
    Dept. of Electr. Eng., Virginia Univ., Charlottesville, VA, USA
  • Volume
    43
  • Issue
    8
  • fYear
    1995
  • fDate
    8/1/1995 12:00:00 AM
  • Firstpage
    1880
  • Lastpage
    1889
  • Abstract
    Given a single record, the authors consider the problem of estimating the parameters of a harmonic signal buried in noise. The observed data are modeled as a sinusoidal signal plus additive Gaussian noise of unknown covariance. The authors define novel higher order statistics-referred to as “mixed” cumulants-that can be consistently estimated using a single record and are insensitive to colored Gaussian noise. Employing fourth-order mixed cumulants, they estimate the sinusoid parameters using a consistent, nonlinear matching approach. The algorithm requires an initial estimate that is obtained from a consistent, linear estimator. Finally, the authors examine the performance of the proposed method via simulations
  • Keywords
    Gaussian noise; harmonic analysis; higher order statistics; parameter estimation; signal reconstruction; spectral analysis; additive Gaussian noise; colored Gaussian noise; covariance; deterministic formulation; fourth-order mixed cumulants; harmonic retrieval; harmonic signal; higher order statistics; linear estimator; mixed cumulants; nonlinear matching; sinusoid parameters; sinusoidal signal; Additive noise; Colored noise; Covariance matrix; Gaussian noise; Higher order statistics; Maximum likelihood estimation; Parameter estimation; Radar signal processing; Signal processing algorithms; White noise;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.403347
  • Filename
    403347