• DocumentCode
    13951
  • Title

    Invariant Observer Design for a Helicopter UAV Aided Inertial Navigation System

  • Author

    Barczyk, Martin ; Lynch, Alan F.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
  • Volume
    21
  • Issue
    3
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    791
  • Lastpage
    806
  • Abstract
    The invariant observer is a recently introduced constructive nonlinear design method for symmetry-possessing systems such as the magnetometer-plus-global positioning system (GPS)-aided inertial navigation system (INS) example considered in this paper. The resulting observer guarantees a simplified form of the nonlinear estimation error dynamics, which can be stabilized by a proper choice of observer gains using a nonlinear analysis. A systematic approach to this step is the invariant Extended Kalman Filter (EKF), which is modified from its originally proposed form and applied to the aided INS example to obtain the observer gains. The resulting invariant observer is implemented onboard an outdoor helicopter unmanned aerial vehicle platform and successfully validated in experiment and demonstrates an improvement in performance over a conventional (non-invariant) EKF design.
  • Keywords
    Kalman filters; autonomous aerial vehicles; design engineering; helicopters; inertial navigation; nonlinear estimation; nonlinear filters; observers; sensor fusion; EKF design; GPS-aided INS; constructive nonlinear design method; helicopter UAV aided inertial navigation system; invariant extended Kalman filter; invariant observer design; magnetometer-plus-global positioning system-aided inertial navigation system; nonlinear analysis; nonlinear estimation error dynamics; outdoor helicopter unmanned aerial vehicle platform; symmetry-possessing systems; systematic approach; Global Positioning System; Helicopters; Magnetometers; Manifolds; Mathematical model; Nonlinear dynamical systems; Observers; Inertial navigation; Kalman filters (KFs); nonlinear systems; observers; sensor fusion; unmanned aerial vehicles (UAVs);
  • fLanguage
    English
  • Journal_Title
    Control Systems Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6536
  • Type

    jour

  • DOI
    10.1109/TCST.2012.2195495
  • Filename
    6203568