Radar Debris Algorithms and Models for Discrimination

Because of the large number of objects in a BMD threat cloud, discrimination of an RV from debris and decoys stresses the radar and processor resources available in the BMDS. During Phase I, MARK Resources developed several relatively simple algorithms for the detection of a physical feature characteristic either of debris or of threat objects, and we demonstrated the feasibility of quickly and efficiently rejecting debris on the basis of its physical rather than statistical characteristics. Using simulated data, we successfully applied these algorithms over a broad range of conditions, in terms of engagement geometry, debris and threat characteristics and motions, and radar parameters. The algorithms were designed so that they will be straightforward to automate. During Phase II, we propose to refine and automate the debris simulation and rejection algorithms developed in Phase I; to demonstrate the fidelity of the debris simulation algorithms and the effectiveness of the debris rejection algorithms through Monte Carlo testing; and to establish the capability of the debris rejection algorithms to work in real time in BMD radar processors. In order to facilitate transition into the BMDS, we have teamed with Raytheon Integrated Defense Systems’ BMDS Integration Program group.