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.
Efficient Attitude Estimation for a Spin-Stabilized Projectile
Journal of Guidance, Control, and Dynamics ; 39 , 2 ; 339-350
2016-02-01
Article (Journal)
Electronic Resource
English
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