• DocumentCode
    1032321
  • Title

    A two-dimensional Prony´s method for spectral estimation

  • Author

    Barbieri, Maria M. ; Barone, Piero

  • Author_Institution
    Dipartimento di Stat., Probabilita e Stat. Applicate, Rome Univ., Italy
  • Volume
    40
  • Issue
    11
  • fYear
    1992
  • fDate
    11/1/1992 12:00:00 AM
  • Firstpage
    2747
  • Lastpage
    2756
  • Abstract
    The problem of estimating the parameters of a model for bidimensional data made up by a linear combination of damped two-dimensional sinusoids is considered. Frequencies, amplitudes, phases, and damping factors are estimated by applying a generalization of the monodimensional Prony´s method to spatial data. This procedure finds the desired quantities after an autoregressive model fitting to the data, a polynomial rooting, and a least-squares problem solution. The autoregressive models involved have a particular nature that simplifies the analysis. In fact, their characteristic polynomial factors into two parts so that many of their properties can be easily determined. Quick estimates of the parameters computed are found by using standard one-dimensional autoregressive estimation methods. An iterative procedure for refining the autoregressive parameters estimates which gives rise to better frequency estimates is also discussed. Some simulation results are reported
  • Keywords
    iterative methods; parameter estimation; spectral analysis; amplitude estimation; autoregressive model fitting; damped two-dimensional sinusoids; damping factors; frequency estimation; iterative procedure; least-squares problem solution; parameter estimation; phase estimation; polynomial rooting; spatial data; spectral estimation; two-dimensional Prony´s method; Damping; Frequency estimation; Parameter estimation; Phase estimation; Polynomials; Signal analysis; Signal processing algorithms; Signal resolution; Signal to noise ratio; Spectral analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.165661
  • Filename
    165661