An algorithm using an extended Kalman filter is presented for estimating the full attitude of a nose-controlled spin-stabilized projectile using magnetometers and a velocity vector estimate with increased computational efficiency. A dynamic model based on the projectile equations of motion is used in the predictor step of the Kalman filter. A new coordinate system is introduced that enables both the process and measurement models of the Kalman filter to be described by linear, slowly time-varying systems. This property is exploited to generate a steady-state Kalman filter which per current knowledge, has never been done for this problem. Both the extended Kalman filter and steady-state Kalman filter are shown to perform well in simulation studies, and the difference in performance between the two filters is very small.


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    Title :

    Efficient Attitude Estimation for a Spin-Stabilized Projectile


    Contributors:

    Published in:

    Publication date :

    2015-08-07


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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