• DocumentCode
    3244478
  • Title

    Altitude information fusion of miniature unmanned helicopter based on LSSVM

  • Author

    Jing, Li ; Wu Jiande ; Yugang, Fan ; Xiaodong, Wang ; Weili, Chen

  • Author_Institution
    Fac. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
  • fYear
    2010
  • fDate
    20-21 Oct. 2010
  • Firstpage
    262
  • Lastpage
    264
  • Abstract
    The miniature unmanned helicopter exhibits a highly nonlinear, high dimensional feature space and uncertain conditions. This paper describes an altitude information fusion method based on Least Squares Support Vector Machine (LSSVM). This method uses small sample without human experience, modeling by the measured data from the GPS and INS. The simulations results have demonstrated the modeling well show the helicopter´s actual altitude in the hover state.
  • Keywords
    Global Positioning System; computerised navigation; helicopters; least squares approximations; remotely operated vehicles; sensor fusion; support vector machines; GPS; INS; altitude information fusion; least squares support vector machine; miniature unmanned helicopter; Education; Least Squares Support Vector Machine (LSSVM); information fusion; miniature unmanned helicopter altitude;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling (KAM), 2010 3rd International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-8004-3
  • Type

    conf

  • DOI
    10.1109/KAM.2010.5646139
  • Filename
    5646139