• DocumentCode
    1468843
  • Title

    Fractional convolution and correlation via operator methods and an application to detection of linear FM signals

  • Author

    Akay, Olcay ; Boudreaux-Bartels, G. Faye

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Dokuz Eylul Univ., Izmir, Turkey
  • Volume
    49
  • Issue
    5
  • fYear
    2001
  • fDate
    5/1/2001 12:00:00 AM
  • Firstpage
    979
  • Lastpage
    993
  • Abstract
    Using operator theory methods together with our previously introduced unitary fractional operator, we derive explicit definitions of fractional convolution and correlation operations in a systematic and comprehensive manner. Via operator manipulations, we also provide alternative formulations of those fractional operations that suggest efficient algorithms for discrete implementation. Through simulation examples, we demonstrate how well the proposed efficient method approximates the continuous formulation of fractional autocorrelation. It is also shown that the proposed fractional autocorrelation corresponds to radial slices of the ambiguity function (AF). We also suggest an application of the fast fractional autocorrelation for detection and parameter estimation of linear FM signals
  • Keywords
    convolution; correlation methods; frequency modulation; mathematical operators; parameter estimation; signal detection; ambiguity function; discrete implementation; efficient algorithms; fast fractional autocorrelation; fractional autocorrelation; fractional convolution; fractional correlation; linear FM signals detection; operator theory methods; parameter estimation; unitary fractional operator; Autocorrelation; Convolution; Fourier transforms; Frequency domain analysis; Optical signal processing; Parameter estimation; Signal analysis; Signal mapping; Signal processing; Signal processing algorithms;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.917802
  • Filename
    917802