Flight attitude estimation for MAV based on M-estimation

Aiming at the attitude measurement based on MEMS (Micro Electromechanical Systems) inertial sensors, this article analyzes the limitations of traditional flight attitude estimate methods applied to MAV (Micro Aerial Vehicle) at first. Then, an extended Kalman filter (EKF) is deduced and constructed with the attitude matrix solving by MEMS gyroscope as the state update and the gravity vector solving by MEMS accelerometer as the observation update. Subsequently, an innovation amendment method based on M-estimate is designed to improve the ability of Kalman filter to resist the interference from carrier maneuvering acceleration. Finally, simulation and prototype testing verify the validity of the algorithm.