• DocumentCode
    2446453
  • Title

    HRR target recognition using the geometry information of scattering centers

  • Author

    Xun, Zhang ; Zhaowen, Zhuang ; Guirong, Guo

  • Author_Institution
    ATR Nat. Lab., Nat. Univ. of Defense Technol., Hunan, China
  • Volume
    2
  • fYear
    1997
  • fDate
    14-18 Jul 1997
  • Firstpage
    936
  • Abstract
    In this paper, a new approach for target recognition is proposed and tested on backscattering returns of high range resolution (HRR) radar. The feature vector is constructed from the geometry information of the scattering centers extracted from the HRR radar returns of targets. It is found that the geometry parameters are more robust to the aspect angle variations than the range profile. The dimension of the feature vector based on the geometry parameters is much smaller than that based on the range profile that can be used as a good feature vector. The algorithm is applied to the recognition of three scaled models of aircraft using a radial basis function (RBF) neural network
  • Keywords
    backscatter; feedforward neural nets; radar target recognition; target tracking; HRR target recognition; aircraft; aspect angle variations; backscattering returns; feature vector; geometry information; high range resolution radar; neural network; radial basis function; range profile; scaled models; scattering centers; Data mining; Diffraction; Frequency; Information geometry; Neural networks; Radar cross section; Radar scattering; Scattering parameters; Solid modeling; Target recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace and Electronics Conference, 1997. NAECON 1997., Proceedings of the IEEE 1997 National
  • Conference_Location
    Dayton, OH
  • Print_ISBN
    0-7803-3725-5
  • Type

    conf

  • DOI
    10.1109/NAECON.1997.622754
  • Filename
    622754