Research On GFSINS/GPS Integrated Navigation System Based On The Six-axis Accelerometer

Inertial navigation systems(INS) play an important role in field of military and defense, especially in field of Aeronautics and Astronautics due to its advantages as great work-autonomy, strong anti-interference ability, etc. Among them, gyro free strapdown inertial navigation system(GFSINS) has been a preferred choice for tactical weapons like missile because it abandoned gyros which have complex structure, poor impact resistance and maintenance. However, most existing GFSINSs are composed of several accelerometers, which leads to the complexity of its angular motion solution, poor precision and high accuracy of installation, etc. In addition, INS's error accumulates with time, which is the key reason why it can only be used in short range navigation.This paper focused on the configuration and error accumulation problem of GFSINS. In view of difficulties of those GFSINSs which had similar configurations, 8-UPS parallel type six-axis accelerometer was introduced as the sensitive element of inertial navigation to form a new type of GFSINS. At the same time, the new GFSINS's position, velocity, attitude and angular velocity equations were derived by using intermediate parameters from the sensor's decoupling algorithm. The simulation and experiment all shown that the new GFSINS can meet navigation requirements of medium accuracy and real-time, especially, it had great precision and efficiency in angular motion solution. But, new GFSINS's error had also accumulated. Under this circumstance, the paper combined GPS which had mature technology and stable precision and new GFSINS into an integrated navigation system in order to correct the navigation error of GFSINS. Based on the derived error equations of new GFSINS, scheme design and mathematical modeling of this integrated navigation system were discussed, also, preliminary data fusion was completed by using Kalman fliter. However, Kalman fliter's application conditions ware very harsh and the existing adaptive fliter didn't conform to the mathematical model of this integrated navigation system. So, the paper proposed an improved integrated filtering model which wouble be suitable for most linear time-varying systems. As to the unknown noise, four kinds of system noise estimation by different angles were derived. By comparison and analysis, an improved adaptive Kalman flitering algorithms based on noise finite memory was obtained which had wide application range, high estimation accuracy and strong robustness, etc. Finally, a test acheme includes indoor and outdoor tests were designed by ultilizing a six-dimensional vobration platform and a car separately to verify the reserched theory. This test scheme could provide full parameter navigation performance test in various motion state. Compared with existing navigation test plan, this scheme had wider test range and lower cost.This paper can provide a new thought to curruent research on GFSINS and a reference solution for surpressing error divergence of proposed GFSINS, also, lays a foundation for the engineering application of the six-axis accelerometer.