Enhancing the Commander's Decision Aid to Network-Centric Platform Protection System Requirements

Since 1995, BAE Systems Electronics, Intelligence & Support (EI&S) has been developing and demonstrating the Commander‘s Decision Aid (CDA), a generalized sensor/information fusion processor and resource/response manager for integrated defense of ground combat vehicles. The CDA was developed under several contracts to Prime Contractor United Defense for the U.S. Army Tankautomotive & Armaments Command (TACOM). The CDA performs sensor fusion, threat typing, prioritization, countermeasure response management, and countermeasure effectiveness. To date, the CDA has been exercised in live-fire exercises against numerous threats at Yuma Proving Grounds, AZ. The next step is extending the CDA to address new requirements in a network-centric operation. Initially the CDA focused on single-vehicle self-defense, the new growth for CDA needs to support network-centric—comprised of support vehicles (e.g., C2, multispectral sensors, weapons, resupply, UAVs, bridge laying, countermine, medical), overhead assets (SATCOM), seismic/acoustic unmanned guided sensors (UGS), and JSTARS. The CDA needs to address a barrage of line-of-sight (LOS) and non-LOS onboard/offboard data. Threats are multispectrally guided and unguided, and the CDA response times will be extremely short, including salvo attacks where the CDA must address simultaneous or near-simultaneous threats. Both cooperative vehicle sensing and countermeasures are required, and handling data with varying levels of accuracy, confidence, time-lines and coordinate systems is required. Responses will include sensor cueing, threat avoidance, and counterfire (use of weapons). Both rural and MOUT (military operations in urban terrain) offer a wide host of challenges for the CDA in that the it needs to respond to ―real‖ threat situations—verses false alarms, spoofing, and real threats that are aimed at other vehicles or misguided. In this paper we review the CDA architecture, its functions, and high-level algorithm set. Next we reveal some of the extended interfaces with the basic data available for processing, and delineate the extensions of the CDA. We close the paper by listing extended CDA challenges.