Distributed Multitarget Search and Track Assignment With Consensus-Based Coordination

This paper presents a distributed, consensus-based approach to optimize radar resource management for ballistic missile surveillance and tracking. Radar search, target detection, and target tracking are described using a nonlinear, three-dimensional model. Target tracking includes an estimate of the resources required to reduce target uncertainty to support engagements. Each radar determines its preferred radar-to-target assignment using a probabilistic optimization algorithm that balances radar loading and minimizes the total radar usage. Under heightened track demand, radar search sectors degrade symmetrically about a designated threat axis. A unique global radar-to-target assignment that is robust to resource estimation error is generated by a distributed consensus algorithm. Performance of the coordinated algorithm is compared with uncoordinated alternatives via Monte Carlo simulations.