An interference power allocation method against multi-objective radars based on optimized proximal policy optimization

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Wenxu Zhang , Yajie Wang , Xiuming Zhou , Zhongkai Zhao , Feiran Liu
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引用次数: 0

Abstract

Aiming at the problem of interference resource scheduling in cognitive electronic warfare, a multi-objective interference power allocation method based on the proximal policy optimization (PPO) framework is proposed in this paper. Firstly, the confrontation between jammers and multi-objective radar networks is mapped as the interaction between the agent and the environment, and the radar target detection model under suppression interference is established. On this basis, an interference power allocation model against multi-objective radars based on PPO framework is constructed. Moreover, a reward normalization mechanism is introduced to optimize the reward setting, and an interference power allocation method based on optimized PPO is proposed. Meanwhile, this paper constructs a confrontation scenario in which the jammer covers the target aircraft to break through the multi-objective radar network. Simulation experiments are conducted based on this scenario to verify the effectiveness of the method proposed in this paper. The interference power allocation method proposed in this paper can intelligently adjust the power allocation scheme of the jammer according to the electromagnetic situation on the battlefield, optimize the resource utilization of the jammer, and occupy the initiative on the battlefield.
基于优化近端策略的多目标雷达干扰功率分配方法
针对认知电子战中的干扰资源调度问题,本文提出了一种基于近端策略优化(PPO)框架的多目标干扰功率分配方法。首先,将干扰机与多目标雷达网络之间的对抗映射为代理与环境之间的相互作用,并建立了压制干扰下的雷达目标探测模型。在此基础上,构建了基于 PPO 框架的多目标雷达干扰功率分配模型。此外,还引入了奖励归一化机制来优化奖励设置,并提出了基于优化 PPO 的干扰功率分配方法。同时,本文构建了干扰机覆盖目标飞机以突破多目标雷达网络的对抗场景。基于该场景进行了仿真实验,以验证本文所提方法的有效性。本文提出的干扰功率分配方法可根据战场电磁态势智能调整干扰机功率分配方案,优化干扰机资源利用率,占据战场主动权。
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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