Distributed Power Allocation for Multiescort Suppressive Jamming via Nash Bargaining Game

Resource allocation is critical in multi-escort suppressive jamming. However, excessive allocation, especially increased transmit power, increases the risk of escort jammers (EJs) being intercepted by enemy radar network. Moreover, centralized resource allocation methods often suffer from high computational complexity and limited robustness. To address these issues, a distributed power allocation method for multi-escort suppressive jamming is proposed. Specifically, the system model includes a motion model for the trajectories of high-value target (HVT) and EJs, a jamming model for EJs power allocation, a detection probability model to quantify the radar network's detection capability, and an interception probability model to assess the likelihood of EJs interception. Based on this, the problem is formulated as a dynamic constrained optimization problem (DCOP), aiming to minimize interception probability under a detection probability constraint. It is further modeled as a Nash bargaining game (NBG), with the existence and uniqueness of the Nash bargaining solution (NBS) theoretically proven, and a distributed power allocation algorithm is proposed based on an alternating iterative approach. Simulation results show that, compared with maximum power and centralized schemes, the proposed method achieves lower interception probability with reduced computational complexity.