Research Attitude Measurement System Of Small Four Rotor UAV

In recent years, with advances in science and technology, particularly the development of micro inertial sensor technology, the original application of high precision and Advanced UAV technology has been expanding, evolving towards the civil field. Now it has been widely used in the border patrol, disaster relief, radiation detection, chemical leak surveys, aerial photography, agricult ure and other fields.UAV attitude is not only the basis of UAV control, but also the core of the navigation.It also has great impact on the stability flight of UAV. With the advantages has low cost, good dynamic performance and light weight, the small four-rotor of UAV becomes the most widely used. However, performance and precision of inertial sensor used on a small four-rotor UAV should be improved, because individual sensor can not meet the requirements of attitude measurement. Gyroscopes is extremely sensitive to attitude change,it can accurate measure angular rate in a short time, but the low cost gyro can cause drift, so it can not achieve attitude measurement for a long time. Accelerometers can also be used to measure attitude, but it could not overcome the interference of UAV accelerated flight, and use accelerometer alone can not measure the yaw, it must cooperate with the magnetometer for the yaw measurements.In order to measure the UAV attitude accurately, this paper designed the attitude measurement system via the gyroscope, accelerometer magnetometer and the data processor, and achieve the fusion of sensor measurements by calculating the accelerometer trust degrees, and using the method of Kalman filter and an attitude solution algorithm. Thus we can estimate the error four quaternion and get attitude Quaternion, then get the the attitude angle of UAV. At the same time, according to the actual hardware condition. This paper also studies the extended Kalman filter based on UD decomposition, which overcomes the effect of rounding error of attitude measurement system effectively. Experiment results show that both kinds of the Kalman filter algorithm can measure the UAV attitude angle accurately in low dynamic flight environment. The two Kalman filter algorithms above have been successfully applied to small quadrotor UAV attitude measurement system.