• DocumentCode
    115081
  • Title

    Fast inertia property estimation via convex optimization for the asteroid redirect mission

  • Author

    Unsik Lee ; Besson, David ; Mesbahi, Mehran

  • Author_Institution
    Dept. of Aeronaut. & Astronaut., Univ. of Washington, Seattle, WA, USA
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    3364
  • Lastpage
    3369
  • Abstract
    Accurate inertia property estimation is critical to the success of the upcoming asteroid redirect mission. The inertia tensor, center of mass, and total mass of the spacecraft-asteroid combined rigid body must be accurately estimated so that solar electric propulsion can be used to redirect an asteroid into an orbit around the Earth. This paper develops an efficient algorithm to solve for those properties. The estimation is framed as a least squares minimization problem subject to convex constraints. A standard least squares approach is not sufficient due to a matrix rank deficiency arising from the fact that a pure torque cannot be applied to the asteroid after capture. The constrained least squares minimization framework allows for fast inertia estimation with a convex optimization solver, in the sense that accurate estimates can be made with only a few force inputs and response measurements. Simulations are performed in MATLAB R2013B using the CVX 2.1 convex optimization solver to assess the algorithm´s performance in a typical mission scenario.
  • Keywords
    asteroids; celestial mechanics; convex programming; electric propulsion; estimation theory; inertial systems; least squares approximations; matrix algebra; minimisation; space vehicles; trajectory optimisation (aerospace); CVX 2.1 convex optimization solver; MATLAB R2013B simulations; asteroid redirect mission; constrained least square minimization framework; inertia property estimation; matrix rank deficiency; solar electric propulsion; spacecraft-asteroid combined rigid body; Accuracy; Force;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7039910
  • Filename
    7039910