Multiscale Information-Driven Radar Resource Algorithm-Level Coscheduling for Joint Maneuvering Target Tracking and Antinoise Suppression Jamming

To enhance maneuvering target tracking and mitigate noise suppression interference under low radar interception probability, by exploiting the intertask reusable information and coupling relationship, the proposed cognitive radar multidimensional resource management (CRMRM) strategy collaboratively optimizes multidimensional signal domains to improve the linked multitask processing capability. First, to characterize comprehensive multitask performance and diversified constraints, the CRMRM-oriented task priority-guided hierarchical criterion function constructs the predictive conditional Bayesian risk lower bound (PC-BRLB) and frequency-domain antijamming reward, while treating the radar interception probability as a secondary constraint, alongside real-time spectrum limitation and resource constraints, to form a multicomponent constraint term. By constructing the subchannel selection action to formalize frequency-domain resource, this reward integrates the tradeoff between bandwidth utilization and interference avoidance, and future multistep reward impact based on state transition. Second, to tackle the underlying high-dimensional multiconstraint problem via criterion characteristic analysis, a multiscale information-driven algorithm-level collaborative iterative solution method is proposed to address discrete and continuous variables separately through strategy decomposition and problem segmentation. The temporal difference (TD) actor critic iteratively performs the TD-error-based policy and value update, addressing the delayed reward and future multistep effect in frequency-domain resource optimization. Leveraging two propositions, the radiated power and dwell time are then jointly analytically optimized under the interception threshold, reducing variable dimension and computational complexity. The improved artificial bee colony handles the PC-BRLB by balancing global exploration and local exploitation, converging to the optimal pulse length and frequency modulation rate. Simulation results confirm CRMRM’s superiority over alternative methods.