• DocumentCode
    865610
  • Title

    On polynomial phase signals with time-varying amplitudes

  • Author

    Zhou, Guotong ; Giannakis, Georgios ; Swami, Ananthram

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    44
  • Issue
    4
  • fYear
    1996
  • fDate
    4/1/1996 12:00:00 AM
  • Firstpage
    848
  • Lastpage
    861
  • Abstract
    We address the parameter estimation problem for a class of nonstationary signals modeled as polynomial phase signals with time-varying amplitudes. Exponentially damped polynomial phase signals are treated as a special case and are analyzed in detail. High-order instantaneous moments provide the basic analytical tool, but links are shown to exist with either the usually employed FFT-based technique or the high-resolution Kumaresan-Tufts (1982), MUSIC, and matrix pencil methods. Asymptotic properties of the relevant estimators are established, Cramer-Rao lower bounds on the amplitude and phase parameter estimates are derived, and computer simulations are carried out to evaluate the performance of various schemes. We focus on parametric modeling of AM-FM signals, mainly because parametric techniques offer parsimony and allow for theoretically unlimited resolution
  • Keywords
    amplitude estimation; amplitude modulation; fast Fourier transforms; frequency modulation; matrix algebra; phase estimation; polynomials; signal resolution; time-varying systems; AM-FM signals; Cramer-Rao lower bounds; FFT based technique; MUSIC; amplitude parameter estimate; asymptotic properties; computer simulations; exponentially damped polynomial phase signals; high-order instantaneous moments; high-resolution Kumaresan-Tufts method; matrix pencil method; nonstationary signals; parameter estimation; parametric modeling; performance evaluation; phase parameter estimate; polynomial phase signals; signal analysis; time-varying amplitudes; Amplitude estimation; Doppler radar; Frequency modulation; Least squares approximation; Maximum likelihood estimation; Parameter estimation; Parametric statistics; Phase estimation; Polynomials; Signal analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.492538
  • Filename
    492538