Application of improved strong tracking Kalman filter in MSINS/GPS integrated navigation system

Through embedded analysis of the calculating principles of suboptimal fading factors, this dissertation puts forward a method of time varying fading factors estimation without a prior knowledge. This method has been used to improve the strong tracking Kalman filter algorithm and applied to loose coupling system of MSINS/GPS integrated navigation. Respectively to fade different data channel with several suboptimal fading factors, it can effectively improve the tracking ability of the filtering algorithm. The simulation results show that this approach can resolve the problem of the measurement correlation and the sensitivity of initial values selecting. The real time character and robust of the system has been improved.