• DocumentCode
    3308826
  • Title

    Invariant Extended Kalman Filter: theory and application to a velocity-aided attitude estimation problem

  • Author

    Bonnabel, Silvère ; Martin, Philippe ; Salaün, Erwan

  • Author_Institution
    Centre de Robot., MINES ParisTech, Paris, France
  • fYear
    2009
  • fDate
    15-18 Dec. 2009
  • Firstpage
    1297
  • Lastpage
    1304
  • Abstract
    A new version of the extended Kalman filter (EKF) is proposed for nonlinear systems possessing symmetries. Instead of using a linear correction term based on a linear output error, it uses a geometrically adapted correction term based on an invariant output error; in the same way the gain matrix is not updated from of a linear state error, but from an invariant state error. The benefit is that the gain and covariance equations converge to constant values on a much bigger set of trajectories than equilibrium points as is the case for the EKF, which should result in a better convergence of the estimation. This filter is applied to the practically relevant problem of estimating the velocity and attitude of a moving rigid body, e.g. an aircraft, from GPS velocity, inertial and magnetic measurements. In this context it can be seen as an extension of the ¿multiplicative EKF¿ often used for quaternion estimation.
  • Keywords
    Kalman filters; attitude measurement; matrix algebra; nonlinear filters; nonlinear systems; velocity measurement; covariance equations; gain matrix; invariant extended Kalman filter; invariant output error; invariant state error; multiplicative EKF; nonlinear systems; velocity aided attitude estimation problem; Aircraft; Convergence; Covariance matrix; Equations; Error correction; Filters; Global Positioning System; Magnetic separation; Magnetic variables measurement; Nonlinear systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
  • Conference_Location
    Shanghai
  • ISSN
    0191-2216
  • Print_ISBN
    978-1-4244-3871-6
  • Electronic_ISBN
    0191-2216
  • Type

    conf

  • DOI
    10.1109/CDC.2009.5400372
  • Filename
    5400372