The Pilot's Associate (PA) program has been initiated to help mitigate the extensive workload of the fighter pilot. The PA must continually monitor and evaluate important aircraft, weapon, and threat systems as well as terrain and weather conditions by means of sensor systems. The data from these systems must be fused together to present the PA with a coherent picture of the environment. One common technique for fusing sensor data uses Kalman filters in a multiple model adaptive filter (MMAF). An improved filter selection technique is presented as part of an advanced MMAF. A knowledge-based system is used to augment the usual selection technique. Preliminary results indicate that this approach helps in situations that are known to cause problems for Kalman filter-based MMAF systems.
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