Vehicle Self-location And Orientation System

The basic function of the vehicle position and azimuth determining system (PADS) is to provide the user with accurate geographical coordinate, azimuth, attitude and other navigation data on an automatic and continuous basis, which are the reference standards for the missile launch. To enhance the vehicle weapon system's fast reaction ability, modern advanced land vehicles are always equipped with PADS.The INS/GPS integrated system constructed by inertial navigation system (INS) and global position system (GPS) can be easily satisfied PADS's need in many land navigation systems, and it becomes a popular research trend in western countries. But for Chinese military application, GPS is not completely reliable. In despite of high accuracy of liquid-floated gyro platform INS, the vehicles have to halt every about 10 minute to execute zero velocity update (ZUPT). Long start-up time, low reliability and inconvenient maintenance limit the application of liquid-floated gyro platform INS in the vehicle weapon system.In this thesis, laser gyro strapdown inertial navigation system (SINS) is selected as core navigation system, and integrated navigation system is developed by integrating SINS with odometer and altimeter. In some special environment, land mark is used to implement error compensation. The PADS presented is entirely autonomous, not reliable to GPS and ZUPT, and the system has high accuracy, fast reaction and high reliability.The main efforts done in this thesis are as follows:1. Based on the inertial measurement unit(IMU) increment output data, SINS algorithms, including attitude updating algorithms, velocity updating algorithms and position updating algorithms, are introduced. By taken into account coning error, sculling error and scrolling error in the attitude, velocity and position updating algorithms respectively, a set of SINS algorithms are well deduced.2. Using the distance increment sample for odometer, high accuracy dead reckoning (DR) algorithms are proposed. DR error model is investigated and similarity theory between true trajectory and DR trajectory is gotten. On the basis of the trajectory similarity method, error compensation algorithms are described, which can compensate for some source errors, including IMU installation errors, odometer scale factor error. By means of a pre-known land mark, the azimuth error of initial alignment can be identified to realize high accuracy navigation.