A Fast Solver for Dwell Time Allocation in a Phased Array Radar

Abstract

The dwell time resource is usually limited when a phased array radar (PAR) tracks multiple targets. In this paper, a fast solver is proposed for the dwell time allocation (DTA) in the cluttered environments. The optimization model is established as minimizing the worst case of position Bayesian Cramér-Rao lower bounds (BCRLBs) among multiple targets under the constraint of total dwell time budget. The BCRLB minimization is hindered by the intractable information reduction factor (IRF) term, which expresses the information loss due to clutter. By replacing the IRF with its upper bound, the probability of detection (PD), we formulate a closed-form objective function-based optimization problem. By using the strictly decreasing property of the BCRLB, two optimal conditions are proposed to obtain a unique subset of the optimal solutions. Then, the remaining parts can be directly set as the lower or upper bounds. Simulation results confirm the competitive performance and computation saving, compared with existing convex optimization-based methods and the sequential relaxation-based method, especially when facing a large number of targets. The target with a lower signal-to-noise ratio (SNR) will be given more dwell time resources.