The Unscented Kalman Filter Estimators for High Dynamic Doppler Shift Environments

摘要

The Extend Kalman Filter (EKF) is widely used in the tracking of high dynamic Doppler shift trajectories, but it has some flows when it is used to estimate the state of nonlinear systems. In this paper, we apply the Unscented Transformation (UT) based Unscented Kalman Filter (UKF) to the state estimating of the high dynamic Doppler environments. Augmented UKF estimator and nonaugemented UKF estimator are designed, which are two versions of the UKF estimators. To compare the performance of the two estimators, they are applied to tracking a common high dynamic trajectory, and we point out that given different conditions, the performance of the estimators will be different.