Radar resource management in a dense target environment

Abstract

The coordination of multifunction phased array radars across networked platforms can enable superior functionality and battle space awareness. This thesis formulates and solves a number of optimization models and heuristic algorithms to analyze and prescribe radar-to-target assignments and schedules. One optimization model uses full target information to provide a best case assessment of the ability of a given set of radar platforms to track a collection of targets. A modified version of this model determines the impact on these results if targets coordinate their maneuvers in order to overwhelm the radar system.We then consider the more realistic scenario in which the planner's knowledge is imperfect and describe approaches for allocating radar assets to targets in that setting. The first such approach extends an existing two-dimensional geographic allocation method to three dimensions. This allows for an allocation of the operating space to radar assets and can serve as a preallocation heuristic for more sophisticated assignment algorithms. Moreover, because the existing method does not account for transfers in tasks between geographical areas, this thesis models the additional workload involved in performing handoffs of targets between radars.