• DocumentCode
    3328473
  • Title

    Wavefront Adaptive Sensing for Radar Spread Clutter Mitigation

  • Author

    Bilik, Igal ; Kazanci, Oguz ; Krolik, Jeffrey

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC
  • fYear
    2007
  • fDate
    12-14 Dec. 2007
  • Firstpage
    185
  • Lastpage
    188
  • Abstract
    In spatially inhomogeneous, Doppler-spread radar environments, adaptive processing is often precluded because neither the target wavefront is sufficiently known nor is signal-free training data available. This paper presents a new clutter mitigation method designed to overcome these challenges by combining minimum variance (MV) adaptive beamforming and blind source separation (BSS) for distributed sources. Wavefront adaptive sensing (WAS) is a hybrid adaptive beamforming approach which uniformly maximizes gain against clutter by avoiding MV signal cancellation due to mismatch at high SNR and poor BSS threshold performance at low SNR. Simulation results are presented for target detection in a multi-mode spread-Doppler over-the-horizon radar scenario.
  • Keywords
    Doppler radar; blind source separation; Doppler-spread radar environments; MV adaptive beamforming; MV signal cancellation; adaptive processing; blind source separation; distributed sources; hybrid adaptive beamforming; minimum variance; multimode spread-Doppler over-the-horizon radar; radar spread clutter mitigation; signal-free training data; target detection; wavefront adaptive sensing; Array signal processing; Blind source separation; Design methodology; Object detection; Performance gain; Radar clutter; Radar signal processing; Signal processing; Source separation; Training data; adaptive beamforming; clutter mitigation; over-the-horizon radar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Multi-Sensor Adaptive Processing, 2007. CAMPSAP 2007. 2nd IEEE International Workshop on
  • Conference_Location
    St. Thomas, VI
  • Print_ISBN
    978-1-4244-1713-1
  • Electronic_ISBN
    978-1-4244-1714-8
  • Type

    conf

  • DOI
    10.1109/CAMSAP.2007.4497996
  • Filename
    4497996