Optimal Sensor Scheduling for Ballistic Missile Defense

Ballistic Missile Defense (BMD) has become increasingly complex, as sophisticated and extensive sensors and defense systems have been developed to detect, track, classify and intercept Tactical Ballistic Missiles (TBMs) throughout each phase of their trajectory. These systems include multiple sensors of various types, which must accomplish diverse time-critical tasks that involve multiple moving targets. Our proposed Phase I research involves the development of a new sensor scheduling algorithm for BMD which will utilize Brown’s algorithm to create and iteratively refine a schedule for multiple sensors to perform tasks relating to multiple moving targets. This algorithm was originally developed to optimally allocate search effort against a single moving target to maximize the probability of detection. However, the main ideas can be modified to create sensor schedules which handle other types of tasks as well. The first iteration of Brown’s algorithm uses myopic conditions to optimally schedule the sensors each successive time step; the subsequent iterations incorporate information gained at other times (future and past) to form a schedule that accounts for long-term conditions. Such a non-myopic schedule is especially important in the BMD scenario wherein careful planning may result in more than one opportunity to intercept certain incoming missiles.