Research On MEMS INS/GPS Integrated Navigation System

MEMS (micro-electro-mechanical system) is the 21st century high-tech frontier technology that integrated a variety of micro-machining technology and developed based on the application of the latest achievements of modern information technology. Currently, the precision of micro-inertial sensors has reached a good level. In foreign countries, they have been widely used in automotive safely and military field. The main component of the design is ADIS 16405 which is produced by Analog, To meet the needs of small UAV, developed a integrated navigation system combined with GPS.The main work of this paper is the signal processing, error modeling and compensation,fusion of multi- sensor data. The specific work of this thesis is as follows:(1) The design and implementation of hardware platform. The FPGA was chosen as the core processor, the interface of hardware was designed according to the characteristics of device. In order to improve the efficiency of the navigation computer, ?C/OS-? embedded operating system was used.(2) The analysis and compensation of MEMS sensor. Firstly, to calibration MEMS gyro and accelerometer, we get the parameters of error model through indoor experiment, and we conducted the Allan variance analysis experiment for the MEMS sensors. Then, Combine MEMS sensors features and the requirement of system designed digital filtering algorithms.Finally, according to the error model of geomagnetic sensor, we calculated the parameters of ellipsoid model. To reduce the compensation error by the irrational distribution of calibration position, we proposed an automatic determination algorithm which is based on fuzzy logic system.(3) The design and implementation of integrated navigation system. In order to get stable and real-time navigation information, we used data fusion algorithm that based on Extended Kalman Filter to integrate velocity and position of two systems. The Extended Kalman Filter was designed based on the characteristics of the integrated navigation system. The realization method of EKF filtering algorithm was presented detailed, and analysis the algorithm through simulation.(4) System test. The IMU calibration and magnetic sensor calibration experiments were conducted in laboratory, the static and dynamic experiments were designed, we can verify the validity of algorithm through the result.Combined with the actual experimental environment and equipment, several tests have carried out, the integrated system has good performance, after initial alignment, the horizontal attitude error and the heading attitude error are less than 0.2° and 0.5°? under the turntable test, the horizontal attitude error are less than 0.4° in static test, the horizontal attitude error are less than 0.5° in dynamic test.