Unscented Kalman Filter for Non-linear Estimation

The extended Kalman filter is one of the most widely used methods for tracking and estimation of non-linear systems through linearizing non-linear models.In recent several decades people have realized that there are a lot of constraints in application of the EKF for its hard implementation and intractability.In this paper a new estimation method is proposed,which takes advantage of the Unscented Transformation method thus approximating the true mean and variance more accurately.The new method can be applied to non-linear systems without the linearization process necessary for the EKF,and it does not demand a Gaussian distribution of noise and what's more,its ease of implementation and more accurate estimation features enables it to demonstrate its good performance in numerical experiments of satellite orbit simulation.