Method for radar target tracking based on sequential unscented Kalman filter

This paper introduces a method for radar target tracking based on Sequential Unscented Kalman Filter(SUKF).In UKF,a minimal set of carefully chosen sample points is used to represent random variables distribution.And when propagated through the true nonlinear system,these sample points capture the mean and covariance accurately to the 3rd order for nonlinear transformation.In order to improve filtering accuracy,SUKF is applied to a radar target tracking system.The Monte Carlo simulation demonstrates that the SUKF has higher filtering accuracy and computational efficiency than conventional Extended Kalman Filte(rEKF).