易伟,,
孔令讲
电子科技大学信息与通信工程学院 成都 611731
基金项目:国家自然科学基金(61771110, U19B2017)，****计划(B17008)
详细信息
作者简介:张大琳(1996–)，女，山西阳泉人。现为电子科技大学信息与通信工程学院在读硕士研究生。主要研究方向为干扰系统资源自适应管理、最优化方法及应用
易伟：易 伟(1983–)，男，四川雅安人。现为电子科技大学信息与通信工程学院教授，博士生导师。主要研究方向为低可观测目标检测跟踪、多雷达协同探测等
孔令讲(1974–)，男，河南南阳人。现为电子科技大学信息与通信工程学院教授，博士生导师，********。主要研究方向为宽带雷达系统技术、雷达系统探测技术、相控阵激光雷达技术
通讯作者:易伟 kussoyi@gmail.com
责任主编：丁建江 Corresponding Editor: DING Jianjiang中图分类号:TN972
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出版历程
收稿日期:2021-06-01
修回日期:2021-07-25
网络出版日期:2021-08-10
Optimal Joint Allocation of Multijammer Resources for Jamming Netted Radar System
ZHANG Dalin,YI Wei,,
KONG Lingjiang
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Funds:The National Natural Science Foundation of China (61771110, U19B2017), The Chang Jiang Scholars Program (B17008)
More Information
Corresponding author:YI Wei, kussoyi@gmail.com
摘要
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。
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
Abstract: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.
Key words:Netted Radar System (NRS)/
Cooperative suppressive jamming/
Robust resource optimization/
Detection probability/
Particle Swarm Optimization (PSO)
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