Multiple Task Hierarchical Fully Adaptive Radar

Abstract

In this paper, we consider a sensor system engaged in multiple tasks: target tracking, classification, and identification of target intent (friend or foe). A hierarchical fully adaptive radar (HFAR) approach is developed that autonomously balances the different task priorities so that the three tasks are completed to human-operator defined performance levels. The system is comprised of two first-tier perception-action cycles (PACs) separately performing tracking and classification and one second-tier PAC determining target intent. The first-tier PACs receive data from the system hardware sensors and pass tracking and classifier perceptions up to the second-tier PAC. The second-tier PAC receives performance goals from the system operator and passes hardware sensing requirements down to the first-tier PACs. Each PAC determines its next action based on its current perception, performance goals, and sensor costs. A simulation example is presented to demonstrate performance.