• DocumentCode
    967567
  • Title

    Spectral Caracterization via Fusing Modified Prony Method with High Resolution Nonparametric Spectral Estimators

  • Author

    Ponce-Dávalos, J.L. ; Shkvarko, Y.V.

  • Volume
    3
  • Issue
    3
  • fYear
    2005
  • fDate
    7/1/2005 12:00:00 AM
  • Firstpage
    255
  • Lastpage
    267
  • Abstract
    In this paper, we present a new approach to high-resolution spectral characterization of the unknown number of spectral line components embedded in colored noise. The addressed method resolves the spectral analysis problem via intelligent fusing the two spectrum estimation paradigms: (i) the parametric line spectral estimation that employs the modified regularized Prony (MORP) method for multi-harmonic signal characterization and (ii) nonparametric spectral estimation. Two nonparametric high-resolution spectral estimation methods are proposed to be fused with the MORP: the minimum variance (MV) and maximum entropy (ME) techniques. Via aggregation of the developed model-based MORP and model-free MV/ME techniques into the fused MORP-MV/MORP-ME resulting method a substantial improvement of the spectral characterization performances is gained when those are applied to characterization/analysis of the composed distributed scenes that contain noised closely spaced spectral lines to be localized with high resolution and accuracy. The simulation results are presented to illustrate the performance enhancement gained with the proposed fused MORP-MV/MORP-ME method.
  • Keywords
    Maximum Entropy (ME) Estimator; Minimum Variance (MV) Estimator Modified Regularized Prony Method (MORP); Spectral Analysis; Bayesian methods; Corona; Gaussian processes; Multiple signal classification; Silicon compounds; Telecommunications; Maximum Entropy (ME) Estimator; Minimum Variance (MV) Estimator Modified Regularized Prony Method (MORP); Spectral Analysis;
  • fLanguage
    English
  • Journal_Title
    Latin America Transactions, IEEE (Revista IEEE America Latina)
  • Publisher
    ieee
  • ISSN
    1548-0992
  • Type

    jour

  • DOI
    10.1109/TLA.2005.1642416
  • Filename
    1642416