Joint Node Selection and Power Allocation Strategy for Multi-Airspace Multi-Target Detection in Multisite MIMO Radar System

Resource management technologies offer significant potential for enhancing system performance. This paper proposed an efficient joint node selection and power allocation (JNSPA) strategy to improve the detection performance of a multisite multiple input multiple output (MIMO) Radar System operating in multi-beam modes under multi-airspace multi-target scenarios. Our approach derives explicit expressions for detection probability based on the Neyman-Pearson criterion, distinctively incorporating the detection probability of fluctuating targets in dynamic multi-airspace environments. Employing the Max-min criterion, we optimize the detection performance of the most challenging targets, aiming to elevate the lower bound of the system's overall performance. Considering the practical resource constraints, the proposed JNSPA is formulated as a discontinuous, non-convex mixed-integer nonlinear problem. To solve this NP-hard problem, a three-stage algorithm is proposed: initial model preprocessing to approximate the problem via the squeeze theorem and continuous relaxation of Boolean parameters, followed by convex optimization in two steps to achieve an approximate optimal solution for node selection, culminating in power allocation through convex optimization to yield the final joint resource optimization solution. Simulation results confirm that our JNSPA strategy offers excellent effectiveness and efficiency with reduced computational burden, achieving near-optimal solutions. Additionally, a sensitivity analysis of the parameters influencing detection performance is presented.