Tracking of ballistic target on re-entry using ensemble Kalman filter

Abstract

In this work, ground radar based ballistic target tracking problem in endo-atmospheric re-entry phase with unknown ballistic coefficient has been solved using ensemble Kalman filter (EnKF). EnKF, a powerful tool in nonlinear estimation, is being extensively used by meteorologist but almost unknown to target tracking community. Performance improvement, and computational burden of EnKF with increasing ensemble size have been studied. Performance of EnKF has been compared with most popular extended Kalman Filter (EKF) in terms of biasness, estimation accuracy, and computational efficiency. The simulation results reveal that the estimation accuracy of EnKF with sufficient ensemble size is much better than EKF.