Situation-Adaptive Rotorcraft Information Filter (SARIF)

Advances in aircraft and weapon capabilities have led to a dramatic increase in the tempo of tactical situations facing the combat rotorcraft pilot, reducing the pilot's available decision time. Furthermore, advances in sensors and communications haveresulted in an explosion in the quantity and complexity of information available to the pilot. The pilot wastes precious time sorting through potentially redundant, irrelevant, or conflicting data; there is too much data and too little time.We therefore propose to develop a Situation-Adaptive Rotorcraft Information Filter (SARIF) to perform semantic-fusion-based correlation for message streams within the Special Operations avionics upgrade program, the Common Aviation Architecture System(CAAS). CAAS is in development by Rockwell Collins, who will support integration of SARIF and CAAS under a separate contract with Special Operations Technology Applications Program Office.SARIF will support pilot situation awareness and reduce pilot workload by filtering and prioritizing messages. It will feature a correlator and a classifier to relate incoming messages to existing knowledge and prioritize messages according to the currenttactical situation and mission plan. SARIF will run on an embedded processor in the CAAS general-purpose processing unit. The output will be to the CAAS world-state database, which drives cockpit displays.SARIF will fit directly into the Special Operations avionics upgrade program, the Common Aviation Architecture System (CAAS). Through collaboration with Rockwell Collins, CAAS prime contractor, SARIF is expected to go to Phase III and be deployed alongwith CAAS on around 200 Special Operations helicopters. Further potential exists for deployment on over 1800 aircraft, should the rest of Army aviation choose to adopt CAAS. In addition there is the potential to deploy on helicopter avionics of other USmilitary services.