• DocumentCode
    2295945
  • Title

    A fuzzy pattern recognition method of radar signal based on neural network

  • Author

    Ting Chen ; Wei Chen

  • Author_Institution
    Unmanned Aircraft Vehicle Teaching & Res. Sect., A A P.L.A., Hefei, China
  • Volume
    3
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1178
  • Lastpage
    1181
  • Abstract
    Radar signal recognition is an important step of radar countermeasure processing. The classical recognition method is called weight distance, in which the feature parameter weights are obtained by expert and then the weight distance of unknown radar signal and signal template in database is computed. For it existing subjectivity in setting of feature parameter weights with classical recognition method, and the computing method of recognition is too simple, all of which make recognition result can´t reflect the true fact objectively. Considering this point, a fuzzy pattern recognition method based on neural network getting weights to radar signal recognition is studied in this paper, the feature parameter weights in this method are fixed on by neural network and then the unknown radar signal is recognized by fuzzy pattern recognition method. Simulation experiment and its result show the method in this paper is practicable and more reliable compared with classical method.
  • Keywords
    electronic countermeasures; fuzzy set theory; neural nets; radar computing; radar signal processing; radar target recognition; database; feature parameter weights; fuzzy pattern recognition method; neural network; radar countermeasure processing; radar signal recognition; signal template; weight distance; Artificial neural networks; Databases; Feature extraction; Pattern recognition; Radar countermeasures; Target recognition; Neural Network; feature parameter; fuzzy pattern recognition; membership function; weight value;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583660
  • Filename
    5583660