EXploitation of Characteristic Information for Threat Evaluation

SciTec and Georgia Tech Research Institute (GTRI) propose to develop novel RF/IR kinematic and feature fusion algorithms for incorporation into the Command, Control, Battle Management and Communications (C2BMC) 8.4 track correlation, discrimination, and lethality characterization algorithms that will allow the system to better exploit data from disparate sensors such as the Army Navy/Transportable Radar Surveillance radar (AN/TPY-2) and the Precision Tracking Space System (PTSS). The goal of the proposed work is to determine how to refine the Multiple Hypothesis Correlator, discrimination fusion, and lethality characterization algorithms within C2BMC/GEM to make the best use of data from the radars and from new IR sensors like PTSS, ultimately in support of its primary functions. Residual sensor biases, short-lived, inconsistent covariances, long propagation times between sensor coverage, and detection/tracking of differing subsets of the overall target set render track correlation in the BMDS a challenging problem for any correlator. However, gains (relative to current C2BMC performance) may be realized via use of advanced and robust features in the track correlation, discrimination fusion, and lethality characterization functions.