The Design And Realization Of High Performance Attitude Measurement Platform

Unmanned Aerial Vehicles (UAV) are the field that full of challenge and have a vast use. It contains attitude measurement, navigation, robot, embedded system and wireless transmission. As the input of the navigation control system, attitude measurement to be high performance, small size and low power is the most important thing. At present, the navigation systems have been developed into a complete system, including Inertial Navigation System (INS), GPS aided INS (GPS/INS) and Vision aided INS (Vision/INS) as well. Because of the unique features, INS has the natural advantage in attitude measurement of UAV, especially the MEMS sensors rising recently. This paper is to introduce how to make a high performance attitude measurement system based on the MEMS sensors as the measure unit and coordinating with the data fusion algorithm.Firstly, this paper has given the base theory of attitude measurement, including common coordinate system and common attitude expression, and then introduce the selection of processor and sensors in detail; hardware design and how to make them up to be a practical attitude measurement platform. That is a key point of this paper. Then, it will introduce the data fusion algorithm KALMAN filter and the nonlinear model of UAV which is the key theory of this paper. According to the EKF, to linearize the nonlinear model, we will obtain the iterative equations and make them into program. Through the attitude measurement platform, we fuse the data from sensors and will get the final attitude. At last, we do a lot of experiment to adjust the parameter of KALMAN filter and complete the system. This paper also indicates the limitation of this system and the improvement which has a practical guide.