Abstract：The Gaussian sum filter refines the non-Gaussian noise stochastic model by Gaussian mixture model(GMM) to improve estimation accuracy. However, the dynamic and complex of the navigation measurement environment brings time-varying characteristics to non-Gaussian noise, resulting in distortion in the filter solution. To solve this problem, we propose a Gaussian sum extended Kalman filter(GSEKF) algorithm, which is improved by adaptive estimation of displacement parameters. We discuss the influence of GMM displacement parameters on the fitting accuracy of non-Gaussian noise, and GMM is refined by displacement parameter adaptive method. These improvements make the GSEKF algorithm more stable. The experimental results show that the proposed algorithm has less fluctuation and stronger anti-interference ability compared to the traditional Gaussian sum filtering algorithm when there is time-varying non-Gaussian noise in GNSS/SINS measurement model, which can further improve the estimation accuracy and stability in practical application.