Impact of the orbital eccentricity on the attitude performance before and after the deorbiting phase for Alsat-1

Due to the presence of periodic forcing terms in the gravity gradient torque, orbit eccentricity may produce large response for the roll, yaw and pitch angles. This paper investigates the influence of the orbit eccentricity on the performance of the attitude determination and control subsystem (ADCS) pointing of passive Low Earth Orbit (LEO) satellites stabilized by a gravity gradient boom or having long appendages before and after the deorbiting operation. The contribution of this work is twofold. First, the satellite attitude dynamics and kinematics are modeled by introducing the orbit eccentricity in the equations of motion of a LEO satellite in order to provide the best scenario in which satellite operators can keep the nominal functionality of LEO satellites with a gravity gradient boom after the deorbiting operation. Second, a Quaternion-based Extended Kalman Filter (EKF) is analyzed when the orbit eccentricity is considered in order to determine the influence of this disturbance on the convergence and stability of the filter. The simulations in this work are based on the true parameters of Alsat-1 which is a typical LEO satellite stabilized by a gravity gradient boom. The results show that the orbit eccentricity has a big influence on the pointing system accuracy causing micro-vibrations that affect the geocentric pointing particularly after the deorbiting phase. In this case, satellites have no orbital correction option. The Quaternion-based Extended Kalman Filter analyzed in this paper, achieved satisfactory results for eccentricity values less than 0.4 with respect to pointing system accuracy. However, singularities were observed for eccentricity values greater than 0.4.     

Real-time sensor fault detection and isolation for LEO satellite attitude estimation through magnetometer data

Attitude estimation is a critical component of the Attitude Determination and Control System (ADCS) of any satellite. It is used to convert the sensor observation data to an estimated attitude using filtering algorithms. However, in the presence of sensor faults, the ADCS fails to achieve the desired attitude accuracy. In this paper, the Fault Tolerant Extended Kalman Filter (FTEKF) is proposed to handle this imperfection. In accordance, various filtering steps are included in the FTEKF design to enhance both attitude estimation and sensor fault detection. The developed algorithm can detect and isolate any unexpected sensor faults in real time, which provides a reliable attitude estimation. A comparative study with the classical and robust Kalman filters is performed through numerical simulations in order to validate the effectiveness of the adopted filter in case of magnetometer fault data.