Adaptive Methods for Target Tracking, and Guidance and Control for the U.S. Ballistic Missile Defense System

Ballistic missiles pose formidable challenges for target tracking and intercept because of their spiraling dynamics and significant maneuverability potential as they re-enter the atmosphere at high speeds. Recent studies have shown that conventional methods to estimation, guidance and control design are unable to guarantee sufficient accuracy against such highly maneuvering targets. This is not unexpected since the coupling between the individual elements is not accounted for completely using the conventional design paradigm, and the separation principle which is implicit in such designs can break down in engagements that require high maneuverability. To meet these challenges we propose developing i) adaptive integrated guidance and control (G&C) designs for increased performance and robustness to uncertain interceptor dynamics, ii) adaptive target-state estimation designs for increased performance and robustness against maneuvering targets, iii) an integrated design method for combining adaptive target-state estimation and adaptive G&C designs for improving overall system performance, and iv) collision avoidance methods to avoid mutual kill-vehicle collisions. The adaptive methods are based on flight proven Neural-Network based adaptive control algorithms. We expect that our strategy for integrated adaptive designs can produce never before achieved levels of lethality for the intercept of future maneuvering targets.