面向组网雷达干扰任务的多干扰机资源联合优化分配方法  

Optimal Joint Allocation of Multijammer Resources for Jamming Netted Radar System

作　　者：张大琳 易伟 孔令讲 ZHANG Dalin;YI Wei;KONG Lingjiang(School of Information and Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China)

机构地区：[1]电子科技大学信息与通信工程学院,成都611731

出　　处：《雷达学报（中英文）》2021年第4期595-606,共12页Journal of Radars

基　　金：国家自然科学基金(61771110,U19B2017);长江学者计划(B17008)。

摘　　要：针对多目标突防组网雷达系统(NRS)场景,该文提出一种面向组网雷达干扰任务的多干扰机资源联合优化分配方法。首先,采用组网雷达在干扰环境中对目标的检测概率作为干扰性能指标;然后,结合不同突防目标的检测性能需求,建立了包含干扰波束和发射功率2个优化变量的资源优化模型,并利用粒子群算法对资源优化问题进行求解;最后,考虑到组网雷达系统参数不确定性带来的检测概率泛化误差,建立了干扰资源稳健优化分配模型。仿真结果表明,该文提出的优化方法能有效压制组网雷达,降低组网雷达对突防目标的检测概率;相比传统方法,稳健方法提升了多干扰机对组网雷达的协同干扰性能,且具有鲁棒性。An optimal joint allocation of multijammer resources is proposed for jamming a Netted Radar System(NRS)in the case of multitarget penetration.First,the multitarget detection probabilities of NRS in the suppressive jamming environment are used as an interference performance metric.Then,the resource optimization model is established,including two optimization variables,namely,jamming beam and transmitting power,considering the detection performance requirements of different targets.Particle swarm optimization is used to solve the resource-optimization problem.Finally,considering the generalization error of the detection probability caused by the parameter uncertainty of the NRS,the robust resource-optimization model is established.The simulation results show that the proposed optimization model is effective in suppressing the NRS and reducing the probability of the penetrating targets detected by the NRS.Compared with the traditional method,the robust algorithm improves the cooperative interference performance of multiple jammers against NRS and is robust.

关 键 词：组网雷达系统 协同压制干扰 稳健资源优化 检测概率 粒子群算法 

分 类 号：TN972[电子电信—信号与信息处理]