面向编队突防的多干扰机协同资源分配方法

Collaborative resource allocation method for multiple jammers in formation penetration

干扰对抗的本质为资源维度的竞争,干扰资源受限的单节点已难以满足实际需求,多节点协同干扰可引入更高维度的干扰资源,已成为未来重要的作战形式。然而,传统协同干扰场景中,各节点采用预设发射模式,会导致干扰资源重复冗余配置,在编队突防背景下存在干扰效果较差的问题。针对此问题,提出了一种性能驱动的多干扰机协同资源分配方法,其核心是通过实时分配多干扰机的发射资源,在相同的资源消耗情况下降低敌方雷达对我方突防目标的跟踪精度。首先,推导了干扰场景下突防目标跟踪的贝叶斯克拉美罗下界,评估了多干扰机协同干扰的性能;而后,结合我方干扰机的资源约束,建立了包含驻留时间变量的多干扰机协同资源优化模型,证明了该模型为凸优化问题,并采用增广拉格朗日乘子法进行了快速求解。仿真结果表明,相比于其他基准方法,所提干扰资源分配方法能够有效压制敌方组网雷达,降低其对我方突防目标的跟踪精度,并且在波束个数受限的约束条件下,所提方法仍然具有较好的干扰效果与快速求解能力。

The essence of jamming countermeasure is competition in the resource dimension.The single node with limited jamming resources is no longer able to meet practical needs.Multi node collaborative jamming can introduce higher dimensional jamming resources,which has become an important form of combat in the future.However,in traditional collaborative jamming scenarios,the use of preset transmission modes by each node can lead to redundant configuration of jamming resources,resulting in poor jamming effects in the context of formation penetration.In response to the above issues,a performance-driven method for collaborative resource allocation of multiple jammers is proposed.Its core is to allocate the transmission resources of multiple jammers in real time,so as to reduce the tracking accuracy of enemy radars on our penetration targets under the same resource consumption.First,this article derives the Bayesian Cramér-Rao Lower Bound for tracking penetration targets in jamming scenarios and evaluates the performance of multi jammer collaborative jamming;Then,based on the resource constraints of our jammers,a multi jammer collaborative resource optimization model including dwell time variables is established,which proves to be a convex optimization problem.The Augmented Lagrangian Multiplier Method is used for fast optimization and solution.Simulation results show that compared to other benchmark methods,the proposed jamming resource allocation method can effectively suppress enemy networked radars,reduce their tracking accuracy towards our penetration targets,and still have a good jamming effect and a fast solving ability under the constraint of a limited number of beams.