• DocumentCode
    2228798
  • Title

    Over-the-horizon radar sea clutter suppression algorithm based on tensor decomposition

  • Author

    Chao Bo ; Hong Gu ; Wei-min Su

  • Author_Institution
    Res. Center of Electron. Eng. Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2013
  • fDate
    5-8 Aug. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    To solve the problem of failure to detect ship targets hampered by strong sea clutter in over-the-horizon radar (OTHR), this article proposes sea clutter suppression algorithm based on tensor decomposition. Firstly, this article builds three-order data tensor utilizing the echo data in one distance unit. Then it solves sea clutter subspace and orientation subspace of data tensor by higher order singular value decomposition (HOSVD). Finally, it utilizes the tensor decomposition to suppress sea clutter of data tensor. Compared with the existed sea clutter suppression of subspace method, the algorithm proposed by this article not only increases the signal to clutter plus noise ratio (SCNR), but also improves the estimated accuracy of ship targets Doppler frequency. The effectiveness of the algorithm is verified through theoretical analysis and simulation results.
  • Keywords
    Doppler radar; frequency estimation; interference suppression; marine radar; object detection; radar clutter; radar detection; ships; singular value decomposition; tensors; HOSVD; OTHR; SCNR; clutter subspace; echo data utilization; higher order singular value decomposition; orientation subspace; over-the-horizon radar sea clutter suppression algorithm; ship target Doppler frequency estimation; ship target detection; signal to clutter plus noise ratio; three-order data tensor decomposition; Clutter; Doppler effect; Frequency measurement; Marine vehicles; Radar clutter; Tensile stress; HOSVD; OTHR; sea clutter; ship detection; tensor decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
  • Conference_Location
    KunMing
  • Type

    conf

  • DOI
    10.1109/ICSPCC.2013.6663983
  • Filename
    6663983