Comparison of recursive and batch processing for impact point prediction of ballistic targets

Abstract

The paper deals with the problem of impact point prediction of ballistic targets (BT) by processing measurements acquired either by 3D surveillance or multifunctional phased-array radars. It is assumed that the radar acquires a limited number of measurements that do not encompass the whole target trajectory; thus the established target track has to be extrapolated ahead in time in order to predict the coordinates of the impact point. In this paper we compare performance of batch (i.e. maximum likelihood estimation, MLE) and recursive (extended Kalman filter EKF and unscented Kalman filter UKF) filtering techniques.