Attitude and gyro bias estimation by SVD-aided EKF

Abstract

This study aims to estimate both angular state and rate gyro biases for a small satellite having multiple attitude sensors. Singular value decomposition (SVD) aided Extended Kalman filter (EKF) attitude estimation algorithm is presented. They are integrated for attitude, angular rate, and gyro bias estimation. Pre-processing the measurements of the sun and magnetic field sensors in the SVD method precomputes Euler angles for EKF. The rotational motion parameters of the satellite and biases of the rate gyro are estimated during the EKF application of the method. In comparison with traditional approaches, pre-processing before EKF makes the filter less complex by having the measurements linear and inherently adaptive. Rate gyro biases are estimated in addition to rotational motion parameters in the presented filter with a high accuracy using an inherent adaptation rule of the pre-processing step. Unscented Kalman Filter in addition to traditional and adaptive versions of EKF are tested under the same conditions for their behavior in unfavorable situations.