• DocumentCode
    3382836
  • Title

    Parameters estimation for multicomponent LFM signals using EMD based fractional Fourier transform

  • Author

    Ye, Yuan ; Qing-fu, Li ; Ying, Fu

  • Author_Institution
    Sch. of Inf. Eng., Beijing Inst. of Fashion Technol., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    28-29 Nov. 2009
  • Firstpage
    488
  • Lastpage
    491
  • Abstract
    This paper have focused on the parameter estimation for multicomponent linear frequency modulation (LFM) signals using EMD based fractional Fourier transform. The proposed method iteratively decomposes the multicomponent LFM signals into monocomponent LFM signals and applies fractional Fourier transform (FRFT) to each LFM component, which is a mapping from the time domain to the fractional Fourier domain. Then the LFM component is detected and the parameters are estimated in terms of the maxima and their locations in the fractional Fourier domain. Simulations show that the proposed method can not only achieve high estimation accuracy but also suppress the corss-terms introduced in other time-frequency distributions (TFDs ).
  • Keywords
    Fourier transforms; frequency modulation; parameter estimation; time-domain analysis; EMD; fractional Fourier domain; fractional Fourier transform; multicomponent LFM signals; multicomponent linear frequency modulation signals; parameters estimation; time-frequency distributions; Chirp modulation; Clothing industry; Computational intelligence; Fourier transforms; Paper technology; Parameter estimation; Radar signal processing; Signal processing; Spread spectrum radar; Time frequency analysis; empirical mode decomposition; fractional Fourier transform; multicomponent LFM signals; parameters estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Industrial Applications, 2009. PACIIA 2009. Asia-Pacific Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4606-3
  • Type

    conf

  • DOI
    10.1109/PACIIA.2009.5406382
  • Filename
    5406382