Aiming at problem of high noise

low precision of inertial measurement unit（ IMU） and low precision of classical attitude solution algorithm

a fused algorithm with complementary filtering and Kalman filtering is proposed. The algorithm establish the state equation model based on differential equation of attitude angle and choose attitude angle after compensation filtering as the observation of system. Use EKF algorithm fused measured data of gyro

accelerometer and electronic compass. To verify that the algorithm is effective

use development board with inertial sensors to test in static and dynamic condition. The results of experiments show that the algorithm fused with complementary filtering and Kalman filtering can constraint drift and noise of attitude angle in static condition and track change of attitude angle quickly in dynamic condition

thus precision of attitude angle estimation is improved.