A Fast Power Allocation Strategy for Multibeam Tracking Multiple Targets in Clutter

Abstract

A collocated multiple-input–multiple-output (MIMO) radar has the ability to track multiple targets in the simultaneous multibeam working mode, where the defocused beams are transmitted to illuminate the whole space, and focused beams are received to extract target information. A fast power allocation (FPA) strategy is put forward in this mode. The predicted posterior Cramer–Rao lower bound (PCRLB) in the cluttered background is slighted relaxed and utilized as the optimization metric. The optimization model is then established as minimizing the worst case of PCRLB under the constraint of total power budget. By using the monotonic decreasing and invertible properties of the relaxed PCRLB, a fast sequential relaxation-based solver is proposed for this problem solving. At each iteration, the proposed solver tests the power allocation (PA) to one target whether should be set as the minimum level. Simulation results show the effectiveness and efficiency of the proposed solver, compared with convex optimization-based methods. The results also imply that the target distance and reflectivity are two main factors that influence the PA in our strategy.