Multiple Model Kalman Filter for Star Sensor Calibration

This paper proposes a novel calibration method for the satellite attitude determination system composed of gyroscopes and star sensors. The main objective is to calibrate the low frequency error (LFE) of the star sensor and improve the attitude determination accuracy. In the proposed method, the frequencies of the LFE are extracted according to the frequency spectrum of the estimate of the gyroscope drift obtained from a Kalman filter (KF); then the amplitudes of the LFE signals with the specific frequencies are identified by using the modified multiple model adaptive estimation (MMAE) algorithm. With the identified frequencies and the corresponding amplitudes, a reference model is obtained to compensate for the effects of the LFE. Simulation result shows that the attitude determination accuracy is improved after the calibration.