Research On The MEMS-IMU/GPS Combined Attitude Measurement System For Micro UAV

UAV is gradually developing towards miniaturization, integration, intelligence, low-cost and low power-consumption,so it is more widely used in military and civilian applications.Due to the structure characteristics of micro UAV,when flying in the air,flight stability is vulnerable to unstable air current and wind speed etc. factors, so in order to ensure the micro UAV flight stability, good performance of the flight control system is key guarantee. Usually the attitude measurement system supplys feedback information for posture stabilization loop,so the attitude measurement system with a good performance is a necessary condition for the stability of the UAV.With the development of technology, MEMS is gradually applied to navigation field. Its low-cost, low power-consumption, miniaturization of the characteristics make the system more compact, especially with the development of MEMS-IMU technology, the sensor and the information processing gradually set in one, so that the inertial system develop towards integration, miniaturization, intelligent direction of development. This makes the application of inertial system more and more widely. This paper focuses on the attitude measurement system with MEMS-IMU in a combination of GPS assisted.Firstly, this paper introduces the background and significance of the research, reviewed the development of UAV technology, MEMS technology, navigation technology and Attitude measurement techniques, briefly introduces the theoretical knowledge of attitude measurement system, including common coordinate system and the corresponding transformation, Kalman filtering and the adaptive Kalman filter algorithm based on exponential fading factor.Secondly, the attitude measurement program was given that achieves attitude measurement by the best estimates of the attitude quaternion and accelerometer and magnetometer as observer. This paper presented a solution of the gravity field and introduces the method of applying GPS to solve the motion acceleration of the body. The scheme of initial alignment of the system was given, and the alignment and attitude updating were realized simultaneously.Again,for the performance of MEMS inertial sensor,the error analysis and compensation of the MEMS gyroscope and accelerometer were carried out. The random error of MEMS gyroscope was identified by using Allan method, and the experimental analysis was carried out. The random drift of MEMS gyroscope was modeled by ARMA, and the adaptive Kalman filtering algorithm based on exponential fading factor was used to compensate the random drift.Then, the principle of positioning and velocity measurement was briefly introduced by GPS, especially the principle of acceleration measurement. The optimal estimation of acceleration was obtained by the adaptive Kalman filtering algorithm based on exponential fading factor and laid the foundation for solution of the gravity field.Finally, system's specific software implementation was given. Through the establishment of the system mathematical model, simulation experiments were carried out through MATLAB software. By comparing the MIMU alone measuring posture and MIMU/GPS integrated attitude determination in conventional Kalman filtering algorithm and based on exponential fading filter effect factor to the adaptive Kalman filtering algorithm,the corresponding analysis was given.