• DocumentCode
    3456892
  • Title

    Multi-sensor Fuzzy Stochastic Fusion Based on Genetic Algorithms

  • Author

    Ji-Xu, Ren ; Jia-Cheng, Song ; Ji-Liu, Hai ; Feng Xiao-Yu

  • Author_Institution
    Hefei Univ. of Technol., Hefei
  • fYear
    2006
  • fDate
    20-23 Aug. 2006
  • Firstpage
    589
  • Lastpage
    594
  • Abstract
    To establish a parallel fusion approach of processing high dimensional information, the model and criterion of multi-sensor fuzzy stochastic data fusion were presented. In order to design genetic algorithm fusion ( the fusion parameter coding ) initial population and fitness function establishing, and fuzzy logic controller designing for genetic operations and probability choosing were complete d. The discussion on the highly dimensional fusion was given. For a moving target with the division of 1.64 (velocity) and 1.75 (acceleration), the precision of fusion is 0.94 and 0.98 respectively. The fusion approach can improve the reliability and decision precision effectively.
  • Keywords
    control system synthesis; fuzzy logic; genetic algorithms; sensor fusion; stochastic processes; fusion parameter coding; fuzzy logic controller; genetic algorithms; multisensor fuzzy stochastic fusion; parallel fusion; Algorithm design and analysis; Data engineering; Design optimization; Fuzzy systems; Genetic algorithms; Genetic engineering; Sensor fusion; Stochastic processes; Testing; Uncertainty; data fusion; fuzzy random; genetic algorithm; multi-sensor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Acquisition, 2006 IEEE International Conference on
  • Conference_Location
    Shandong
  • Print_ISBN
    1-4244-0528-9
  • Electronic_ISBN
    1-4244-0529-7
  • Type

    conf

  • DOI
    10.1109/ICIA.2006.305779
  • Filename
    4097723