A linear attitude fusion algorithm for mini autonomous helicopter

A linear attitude fusion algorithm for mini autonomous helicopter was presented. By choosing gravity field and earth magnetic field in body frame as the attitude parameters, the vector observation equation and the attitude kinematics equation including drift error model of gyro were derived. Then an attitude fusion algorithm based on state correlated kalman filter was proposed and the correlation between gyro noise and state variable was resolved. Compared to quaternion parameters, the state equation and observation equation of the proposed attitude parameters possess better linearity. The Monte-Carlo simulations and calculation amount analysis of the algorithm have shown that the proposed algorithm possess higher attitude estimation precision than linear quaternion estimation algorithm in the event of equivalent computational efficiency, and is especially applicable to mini autonomous helicopter.