Resource management for radar tracking

Radar tracking systems are complex and dynamic with both radar and computing resources being shared by a large number of tasks with widely varying requirements. Managing these tasks so as to obtain the maximum benefit from the available resources is a difficult challenge. Environmental factors such as noise, heating constraints of the radar and the speed, distance and maneuverability of tracked targets dynamically affect the mapping between the level of service and resource requirements. In this paper, we present an integrated QoS (quality of service) optimization and dwell scheduling scheme for a radar tracking system. The QoS manager in a radar system must be adaptive, responding to dynamic changes in the environment by efficiently reallocating resources to maintain an acceptable level of service while at the same time satisfying radar constraints such limits on heat dissipation. We utilize an approach we call Q-RAM (QoS resource allocation model). Using convex optimization techniques and an abstract concept called "cool down time", Q-RAM is capable of determining a near-optimal configuration for over 100 radar tasks in less than one second.