• DocumentCode
    2227352
  • Title

    Radar active blanket jamming sorting based on resemblance coefficient cluster

  • Author

    Tang Zhu ; Zhang Bing ; Li Guang-qiang ; Zhang Chen-long

  • Author_Institution
    Dept. of Grad. Manage., Air Force Early Warning Acad., Wuhan, China
  • fYear
    2013
  • fDate
    5-8 Aug. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A sorting method based on resemblance coefficient cluster is put forward to effectively improve the sorting accuracy of radar active blanket jamming. In the method, resemblance coefficient of blanket jamming is used to replace traditional Euclidean distance; resemblance entropy index is deemed as the symbol for whether iteration comes to an end or not. Besides, K-means classifier is improved accordingly. Improved clustering classifier is used for sorting of radar blanket jamming signals. Simulation experiment proves that the method can improve identification rate of types of radar blanket jamming signals in an efficient way and it is characterized by excellent universality.
  • Keywords
    jamming; radar signal processing; radar tracking; sorting; K means classifier; clustering classifier; radar active blanket jamming sorting; resemblance coefficient cluster; resemblance entropy index; Accuracy; Entropy; Frequency modulation; Jamming; Noise; Radar; Sorting; Resemblance coefficient; blanket jamming; cluster; identification;
  • 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.2013.6663924
  • Filename
    6663924