Attitude and heading measurement system and its data fusion method

Attitude and heading information is very important for micro-unmanned air vehicle(MUAV).In this paper,a low-cost micro attitude and heading measurement system is designed using MEMS inertial sensors.To overcome shortcomings such as low precision and easy divergence,a data fusion method with the reduced computational complexity is designed,by which the information from accelerometers,magnetometers and gyroscopes is fused.The pitch angle error,roll angle error and yaw angle error of the system are estimated with Kalman filter.Criterions of data fusion are provided to adjust the measurement information in the Kalman filter equations so that the system can be used while the MUAV is flying in invariable height.Experiment results show that the system can update the parameters of attitude and heading at the rate of 100 Hz,the measurement error is less than 0.6°,and the standard deviation of attitude and heading measurements is less than 0.09°.Moreover,the autonomous flying tests on a fixed wing aircraft by using the system successfully finish the predetermined flight mission.