Non-Myopic Optimization-Based Algorithm for Scheduling in ESA Radars

This paper proposes a novel non-myopic technique for multitarget track scheduling in electronically scanned array radars. The real-time scheduling problem is addressed based on two-level decomposition. For each track task, the minimum expected load state is defined by its target maneuver model. The optimal set of targets which should be updated at the upcoming scheduling interval is calculated by solving a stochastic optimization problem, i.e., based on the minimum expected load states and the system workload. A numerical example is presented with different target densities and maneuvers scenarios. The simulation results show that the proposed approach can significantly decrease track drop rate and increase track accuracy in comparison with the myopic approach.