Mulit-Agent Adaptive Feature Tracking and Discrimination (MAAFTD)

"Effective Ballistic and Theater Missile defense requires that data be fused from all available sensors leveraging the unique capabilities of each sensor and its features. Until now, improvements in sensor resolution and discrimination technologies havebeen looked at to provide the required fusion and target discrimination. It is thesis of this proposal that additionally, new adaptive approaches to such fusion and distributed battle management are required. A technical approach is needed that iscapable of producing adaptive component behaviors between sensors that will optimize reliability and convergence of multiple data from multiple sensors in such systems. FORELL is proposing that BMDO Project Hercules utilize an adaptive intelligent agentapproach with Ballistic Missile Defense architecture sensor component related decision networks to enhance Ballistic Missile tracking and target discrimination. A multi-agent system will aggregrate feature sets based on processed signal data fromindividual sensors and transform those sets into Decision Feature sets. The Decision Feature sets are processed in a Decision Model that is capable of learning decision rules and that generates tracking and discrimination outputs for use in engagementdecisions and for feedback and tuning the sensor front ends. This approach to fusion for missile tracking and discrimination relies on the principles of Simulation-Based Engineering of Complex Adaptive