Research Of Filter Algorithm In Integrated Navigation System Based On Nonlinearity Model

The integrated navigation system of Strapdown Inertial Navigation System(SINS) and Global Positioning System(GPS) is an ideal integrated mode, which has advantages of low cost, high precision, and good reliability, since it has integrated the advantage of good reliability of SINS and high precision of GPS. SINS/GPS integrated navigation system usually has two integrated mode, one is loosely coupled mode, the other is tightly coupled mode. Which the tightly coupled mode has higher precision than the loosely coupled mode. Since the tightly coupled mode used original measurement information which did not have correlation of measurement input information. The thesis researched the filter algorithm of tightly coupled integrated navigation system, and a simulation system was established in order to test the effect of the filters.First the thesis introduced present situation of the integrated navigation system, then the basic principle of SINS and GPS was introduced. The error model of SINS and GPS was established, and the application of kalman filter in SINS/GPS integrated navigation system had be described. Secondly, the integrated mode of integrated navigation system was researched.The principle and the characteristics of the integrated navigation system was mainly described, then different status equations and measurement equations was established according to different characteristics of various kalman filters.Finally, the SINS/GPS semi-physical simulation integrated navigation system according to tightly coupled mode was established. The carrier locus had be simulated by mathematical method, the output results of gyroscope and accelerometer were simulated, then the results be integrated with GPS data in order to establish integrated navigation system. Kalman Filter, Adaptive Filter and Unscented Kalman Filter(UKF) were designed . Experiment results shows that UKF is more suitable to tightly coupled integrated navigation system, it can improve the precision of the system and make the system more optimal.