A Nonlinear Kalman Smoothing Method for Ballistic Target Tracking
Panlong Wu, Jianshou Kong, Yuming Bo, Bing Li · 2009
In order to track the ballistic target more accurate, a suitable model of ballistic target motion is developed and a new nonlinear smoothing method is presented in this paper. The new nonlinear smoothing method named UKS is based on the combination of unscented Kalman filter (UKF) and Rauch-Tung-Striebel (RTS)smoothing method. The UKS method improves the tracking accuracy, and enhances the filtering convergence. The simulation of the application of UKS and UKF methods to track Ballistic target is done separately. The simulation results show that the new method outperforms UKF in terms of tracking accuracy and filter credibility.