• DocumentCode
    1096080
  • Title

    Sweep signal time-delay estimation with time-frequency cross-correlation algorithm

  • Author

    Jiang, Z.J. ; Cui, T.J.

  • Author_Institution
    State Key Lab. of Millimeter Waves, Southeast Univ., Nanjing
  • Volume
    2
  • Issue
    2
  • fYear
    2008
  • fDate
    4/1/2008 12:00:00 AM
  • Firstpage
    121
  • Lastpage
    126
  • Abstract
    Sweep signal is usually employed as a source signal in active detection such as radar and sonar. Since the frequency spectrum of the sweep signal varies against time, a novel algorithm, namely a time-frequency cross-correlation (TFCC) algorithm based on wavelet packet transform (WPT), is proposed to estimate the time delay of sweep signal. In this algorithm, the source sweep and the received signals are decomposed with WPT to obtain their time-frequency representations and the TFCC between the source sweep and the received signals is performed. Each reflected sweep in the received signal is converted into a time-frequency correlation peak whose position can indicate its time delay. The TFCC algorithm can suppress ambient noise effectively and improve the performance of sweep extraction and can match more precisely the source and the reflected sweeps to their known time-frequency characters. Numerical experiments were performed to compare the performance of the TFCC algorithm with that of the conventional cross- correlation and phase-data algorithms. The results proved that the TFCC algorithm can extract the reflected sweeps effectively and its performance is better than that of the conventional algorithms.
  • Keywords
    correlation methods; delays; signal detection; time-frequency analysis; wavelet transforms; WPT; sweep signal time-delay estimation; time-frequency cross-correlation algorithm; wavelet packet transform;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar & Navigation, IET
  • Publisher
    iet
  • ISSN
    1751-8784
  • Type

    jour

  • DOI
    10.1049/iet-rsn:20070076
  • Filename
    4469863