• DocumentCode
    1765938
  • Title

    Radar Signature Analysis Using a Joint Time-Frequency Distribution Based on Compressed Sensing

  • Author

    Whitelonis, Nicholas ; Hao Ling

  • Author_Institution
    Univ. of Texas at Austin, Austin, TX, USA
  • Volume
    62
  • Issue
    2
  • fYear
    2014
  • fDate
    Feb. 2014
  • Firstpage
    755
  • Lastpage
    763
  • Abstract
    A previously proposed time-frequency distribution based on compressed sensing (CS) is applied to radar backscattered signals for signature analysis. The CS joint time-frequency (CSJTF) distribution is based on the Wigner-Ville distribution, but employs CS to remove undesirable cross terms. To adapt the algorithm for radar signals, we develop a search procedure to find the optimal region in the ambiguity plane for achieving the best CSJTF distribution. The algorithm is then applied to backscattering data from several structures of interest, including a pipe, rotating turbine blades, and a moving human. The performance of the CSJTF is compared to that of the short-time Fourier transform and the reassigned spectrogram, and its limitations in time-frequency localization and resolution are discussed.
  • Keywords
    Fourier transforms; backscatter; blades; compressed sensing; radar signal processing; turbines; Wigner-Ville distribution; backscattering data; compressed sensing; joint time-frequency distribution; moving human; pipe; radar backscattered signals; radar signals; radar signature analysis; rotating turbine blades; short-time Fourier transform; time-frequency localization; Backscatter; Doppler effect; Fourier transforms; Radar; Spectrogram; Time-frequency analysis; Wind turbines; Compressed sensing; joint time-frequency distribution; radar signature;
  • fLanguage
    English
  • Journal_Title
    Antennas and Propagation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-926X
  • Type

    jour

  • DOI
    10.1109/TAP.2013.2291893
  • Filename
    6671387