Integrated Vehicle Navigation Based On MEMS Inertial Sensors

With the continuous development of the urban construction and transportation, the resulting traffic problems become more and more serous and receive much concern. Vehicle navigation system, which is one of the key parts of Intelligent Transportation System (ITS), develops rapidly in recent years. Along with the MEMS technology developing, the application of MEMS inertial sensors in vehicle navigation and positioning system appears to be the focus in current research. In the thesis, a great deal of research work on GPS/DR integrated vehicle navigation system based on MEMS accelerometer and gyroscope has been done.Firstly, the positioning principium of GPS and DR is analyzed, then the implementation scheme of GPS/DR integrated navigation system based on MEMS inertial sensors is investigated. In the scheme, DR system is composed of H48C accelerometer and ADXR300 gyro. The coordinates and their conversion which are used in vehicle navigation are analyzed to provide the basis for the navigation algorithm.The H48C 3-axis accelerometer and the ADXR300 gyroscope, which are both MEMS inertial sensors, are used in the GPS/DR integrated vehicle navigation system. The characteristics of the sensors'output signals are analyzed using AR model spectrum estimation method. Furthermore, the error models of the accelerometer and gyroscope are investigated to improve the precision of the DR system. The six-position and angle rate testing method are used to model and compensate the deterministic error. Correspondingly, the wavelet method is utilized for the stochastic error compensation. Through compensating the error source, the positioning accuracy of DR system has been improved effectively.Integrated navigation algorithm is the core of the vehicle navigation system. The principium and structure of Kalman Filtering is introduced. Based on the moving vehicle dynamic model, a Kalman filter is designed through indirect method to fuse the navigation information of GPS and DR system, thus the performance of the integtated system is improved.All the theories and algorithm presented are well tested by the GPS/DR integrated vehicle navigation system recommended in the thesis in HongKong and Nanjing.