• DocumentCode
    1723957
  • Title

    A Multi-parameter Synthetic Signal Sorting Algorithm Based on Clustering

  • Author

    Zhifu, Yu ; Fei, Ye ; Jingqing, Luo

  • Author_Institution
    PLA, Hefei
  • fYear
    2007
  • Abstract
    Radar signal sorting is one of important techniques in electron reconnaissance signal processing and generally uses PRI, RF, DOA, PW, PA and pulse-inner characteristics and so on parameters. Traditional signal sorting is a serial regulation detection system and has some limitation. Especially for a great lot of complicated data, it will be useless. Clustering is an important technique of data mining. It can divide data objects into several classes or clusters based on the comparability of data objects. So a multi-parameter synthetic signal sorting algorithm based on clustering is proposed in order to overcome the limitation of traditional radar signal sorting algorithm. This algorithm makes use of the clustering technique of data mining and combines with DOA diluting algorithm and PRI sorting algorithm, so it can be applied to signal sorting of general radar and special radar. In the end of paper, the simulated experiments show that the synthetic algorithm is effective.
  • Keywords
    data mining; pattern clustering; radar signal processing; signal detection; DOA diluting algorithm; PRI sorting algorithm; clustering; data mining; electron reconnaissance signal processing; multiparameter synthetic signal sorting algorithm; radar signal sorting; serial regulation detection system; Clustering algorithms; Data mining; Electrons; RF signals; Radar signal processing; Radio frequency; Reconnaissance; Signal processing; Signal processing algorithms; Sorting; DOA diluting; PRI sorting; Radar signal; clustering; synthetic sorting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-1136-8
  • Electronic_ISBN
    978-1-4244-1136-8
  • Type

    conf

  • DOI
    10.1109/ICEMI.2007.4350692
  • Filename
    4350692