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The fusion algorithm of SINS/GPS integrated navigation system is mainly based on kalman filter. Kalman filter is the optimal estimation on the conditions that system model and random noise information are accurately known. In practice, most system model and random noise information are not completely known, which may lead to filter estimation accuracy decline. Aiming at this problem, this paper improves the traditional adaptive fading kalman filter according to the method of solving forgetting factor, and proposes an improved adaptive fading kalman filter. The improved algorithm respectively applies in the cases that system noise statistical model cannot be accurately known and measurement noise statistical models cannot be accurately known, respectively corresponding to the two filter algorithms. What’s more, they have a unified filter framework. The simulation results show that the improved adaptive fading kalman filter is more accurate than kalman filter and it can effectively solves the accuracy decline problem caused by the inaccurate noise model.