An efficient micro-satellite attitude estimation algorithm based on QUEST and UD-MEKF

This paper designed an efficient algorithm for attitude estimation using the information from the sun sensors/ magnetometers/ Micro-Electro-Mechanical System (MEMS) gyroscopes. The proposed algorithm uses the Quaternion Estimator (QUEST) and multiplicative extended Kalman filter (MEKF) with Upper triangular matrix-Diagonal matrix (UD) factorization to reduce computational complexity, thereby achieving a real-time attitude estimation. Firstly, the QUEST uses the measurement information from sun sensors and magnetometers to generate a coarse attitude. Then, these estimated values are used as quaternion measurements in the MEKF algorithm. UD factorization is used in the filter to reduce the computational burden. Additionally, the estimated quaternion is fed into the QUEST to determine the initial value of the iteration, thus improving the convergence speed. The simulation results show that the designed algorithm is effective and the attitude estimation accuracy meets the requirements for microsatellites.