首页|面向多任务动态场景的雷达与干扰空时协同波束联合优化方法

面向多任务动态场景的雷达与干扰空时协同波束联合优化方法

扫码查看
原文链接
  • 万方数据
  • 维普
现代雷达对抗形势复杂多变,体系与体系的作战已成为基本特点,而体系整体性能关乎着战场的主动权乃至最终的胜负.通过优化体系中雷达与干扰波束资源可以提升整体性能,获得在空间、时间域优效的低截获探测性能,然而空时域协同波束联合优化是一个复杂多参数耦合的非凸问题.该文针对空时域多任务动态场景,建立了以雷达探测性能为优化目标,以干扰性能以及能量限制为约束条件的优化模型.为求解该模型,该文提出了基于迭代优化的空时协同波束联合设计方法,即以雷达发射、接收、多干扰机发射波束交替迭代优化.其中,针对多干扰机协同优化的不定矩阵二次约束二次规划(QCQP)问题,该文基于可行点追踪-连续凸逼近(FPP-SCA)算法,在SCA算法的基础上,通过引入松弛变量与惩罚项,保证算法在合理松弛度下的可行性,解决了矩阵不定情况下难以获得可行解的问题.仿真表明,在一定的干扰机能量约束下,该文所提方法在保证雷达高性能探测目标且不受干扰情况下,同时实现了多干扰机在空时域干扰对方每个平台以掩护我方雷达探测的效果;相比传统算法,在动态场景中基于FPP-SCA算法的协同干扰具有更优效果.
Joint Optimization of Radar and Jammer Space-time Cooperative Beamforming for a Multitasking Dynamic Scene
The modern radar confrontation situation is complex and changeable,and inter-system combat has become a basic feature.The overall system performance affects the initiative on the battlefield and even the final victory or defeat.By optimizing the beam resources of radar and jammers in a system,the overall performance can be improved,and the effective low-intercept detection effect can be obtained in the spatial and temporal domains.However,joint optimization of cooperative beamforming in the spatial and temporal domains is a nonconvex problem with complex multiparameter coupling.In this paper,an optimization model is established for a multitasking dynamic scene in the spatial and temporal domains.Radar detection performance is the optimization goal,while the interference performance and energy limitation of jammers are the constraints.To solve the model,a joint design method of space-time cooperative beamforming based on iterative optimization was proposed;that is,iterative optimization of radar transmitting,receiving,and multiple jammers transmitting beamforming vectors was alternately optimized.To solve the Quadratically Constrained Quadratic Programs(QCQP)problem with indefinite matrices for multijammer collaborative optimization,this paper is based on the Feasible Point Pursuit Successive Convex Approximation(FPP-SCA)algorithm.In other words,on the basis of the SCA algorithm,algorithm feasibility is ensured through reasonable relaxation by introducing relaxation variables and a penalty term,which solves the difficulty of obtaining a feasible solution when a problem contains indefinite matrices.Simulation results show that under the constraint of certain jammer energy,the proposed method achieves the effect of multiple jammers interfering with each enemy platform in the spatial and temporal domains to cover our radar detection.This effect is achieved while ensuring high-performance radar detection of the target without interference.Compared with traditional algorithms,the collaborative interference based on the FPP-SCA algorithm exhibits a better performance in the dynamic scene.

Radar and jammer resourcesSpace-time beamforming joint optimizationMultiparameter coupling nonconvex problemIterative optimizationFeasible Point Pursuit Successive Convex Approximation(FPP-SCA)

廖晓容、孙国皓、钟苏川、余显祥、李明

展开 >

四川大学空天科学与工程学院 成都 610207

机器人卫星四川省重点实验室 成都 610207

电子科技大学信息与通信工程学院 成都 611731

电子科技大学长三角研究院(衢州) 衢州 324003

展开 >

雷达与干扰资源 空时波束联合优化 多参数耦合非凸问题 迭代优化 可行点追踪-连续凸逼近(FPP-SCA)

国家自然科学基金四川省自然科学基金衢州市大科创项目

622013712022NSFSC19522022D013

2024

10.12000/JR23243

雷达学报
中国科学院电子学研究所 中国雷达行业协会

雷达学报

CSTPCD北大核心EI
影响因子：0.667
ISSN：2095-283X
年,卷(期)：2024.13(3)
  • 14