Classification and Launch-Impact Point Prediction of Ballistic Target via Multiple Model Maximum Likelihood Estimator (MM-MLE)

Abstract

The paper deals with the problems of (i) launch and impact point prediction (LPP, IPP) of ballistic targets (BT) and (ii) BT classification 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 (plots) 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. A procedure based on multiple model maximum likelihood estimator (MM-MLE) has been conceived and tested using a Monte Carlo simulation approach; the parameters selected for testing are the probability of BT correct classification (Pcc), the IPP and the LPP. The new procedure is compared with the estimator described in A. Farina et al. (2004).