Kalman Filter for Spinning Spacecraft Attitude Estimation

This paper presents a Kalman filter using a seven-component attitude state vector comprising the angular momentum components in an inertial reference frame, the angular momentum components in the body frame, and a rotation angle. The relatively slow variation of these parameters makes this parameterization advantageous for spinning spacecraft attitude estimation. The filter accounts for the constraint that the magnitude of the angular momentum vector is the same in the inertial and body frames by employing a reduced six-component error state. Three variants of the filter, defined by different choices for the reduced error state, are tested against a quaternion-based filter using simulated data for the THEMIS mission. The infinitesimal attitude error angles are components of the error state in two of these variants, facilitating the computation of measurement sensitivity matrices and causing the usual 3×33×3 attitude covariance matrix to be a submatrix of the 6×66×6 covariance of the error state. These variants differ in their choice for the other three components of the error state, using either the angular momentum errors in the spacecraft body frame or in the inertial frame. The latter variant shows the best combination of robustness and efficiency in the simulations. Attitude estimation results using THEMIS flight data are also presented. [PUBLISHER ABSTRACT]