Enumeration PCRLB-Based Power Allocation for Multitarget Tracking With Colocated MIMO Radar Systems in Clutter

An effective resource allocation strategy can maximize the remote sensing performance of radar systems, such as target detection and tracking. In this article, two typical power allocation (PA) strategies are developed for the multitarget tracking (MTT) task in colocated multiple-input-multiple-output (C-MIMO) radar systems with the consideration of the clutter. The multibeam concept and the posterior probability density function (pdf) fusion are adopted by the C-MIMO radar system to obtain the global posterior distribution. Specifically, each radar generates multiple simultaneous beams with controllable power during each interval. To ensure that the limited system resources can be utilized effectively, the online PA scheme is implemented according to the prior knowledge predicted from the tracking cyclic recursive feedback results. The posterior Cramer-Rao lower bound (PCRLB) is derived by enumerating all possible target detection and false alarm occurrence cases, and is utilized as the tracking performance metric since it provides a more accurate lower bound on the target state estimation in clutter. Besides, to solve the computationally expensive problem of this PCRLB caused by enumeration operation, we propose a two-step approximate approach. Then, combined with the system resource configuration, two different types of resource optimization problems are designed, namely, performance maximization for a fixed power budget and direct resource minimization. These formulated PA problems are shown to be nonconvex and nonlinear. Therefore, we further propose a modified particle swarm optimization (MPSO) algorithm to solve these problems efficiently. Simulation results verify the superiority and effectiveness of the proposed PA strategies in terms of tracking performance in clutter.