• DocumentCode
    3664419
  • Title

    Target type recognition algorithm for SAR image based on multi-feature fusion classifier of KPFD

  • Author

    Yingying Kong;Weiyang Chen;Henry Leung

  • Author_Institution
    College of information science and technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
  • fYear
    2015
  • fDate
    5/1/2015 12:00:00 AM
  • Firstpage
    435
  • Lastpage
    439
  • Abstract
    Due to the presence of speckle, the target recognition algorithm of SAR image is different from other algorithms. There exists nuances in the detail of type recognition. This paper proposes Multi-feature fusion classifier of KPFD. Based on data from MSTAR database, the results of experiment show the new algorithm is more effective than other 5 kinds of recognition algorithm and recently recognition algorithm. In addition, when the KPFD recognition algorithm is combined with feature fusion classifier in the decision level and measure level, the feature fusion classifier brings good performance on the identification of the types of tank by using Naive Bayesian Classification algorithm(NBC). The recognition rate is up to 87%.
  • Keywords
    "Feature extraction","Classification algorithms","Target recognition","Kernel","Synthetic aperture radar","Mathematical model","Signal processing algorithms"
  • Publisher
    ieee
  • Conference_Titel
    Electronics Information and Emergency Communication (ICEIEC), 2015 5th International Conference on
  • Print_ISBN
    978-1-4799-7283-8
  • Type

    conf

  • DOI
    10.1109/ICEIEC.2015.7284576
  • Filename
    7284576