I. Introduction
The Kalman filter (KF) has been widely used in many applications since it was proposed, such as navigation, signal processing and target tracking. As an online and recursive state estimator, KF is optimal when the state-space model is linear Gaussian [1], [2]. However, in the case of inaccurate noise statistics and/or non-Gaussian noises, the estimation accuracy of KF will be seriously affected. The non-Gaussian noises cannot be modeled accurately by the uniform probability density function (PDF), and the posterior PDF usually has no analytical solution, it is very difficult to design a non-Gaussian filter [3], [4].