• DocumentCode
    1606562
  • Title

    The Data Fusion Techniques for Tasks Ranking in Multifunction Radar

  • Author

    Kawalec, Adam ; Komorniczak, W. ; Pietrasinski, J. ; Czarnecki, Witold

  • Author_Institution
    Mil. Univ. of Technol., Warsaw
  • fYear
    2006
  • Firstpage
    195
  • Lastpage
    198
  • Abstract
    The paper presents the problem of tasks ranking in multifunction radar resources management. The data fusion tasks ranking approach is discussed. The neural network, fuzzy inference system, hybrid fuzzy-neural and fuzzy-probabilistic ranking algorithms are presented. The information sources for tasking process have been selected and discussed. Evaluation of the performance of the ranking process is based on defined costs of removal/delay measures. The testing results are shown and discussed.
  • Keywords
    fuzzy neural nets; inference mechanisms; learning (artificial intelligence); probability; radar computing; resource allocation; sensor fusion; data fusion technique; fuzzy inference system; fuzzy-probabilistic ranking algorithm; hybrid fuzzy-neural network; multifunction radar resources management; registered data learning set; tasks ranking algorithm; Costs; Fuzzy neural networks; Fuzzy systems; Inference algorithms; Intelligent networks; Neural networks; Optimal control; Radar; Resource management; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Microwaves, Radar & Wireless Communications, 2006. MIKON 2006. International Conference on
  • Conference_Location
    Krakow
  • Print_ISBN
    978-83-906662-7-3
  • Type

    conf

  • DOI
    10.1109/MIKON.2006.4345138
  • Filename
    4345138