电讯技术2026，Vol.66Issue(9)：1456-1463,8.DOI:10.20079/j.issn.1001-893x.250415006
基于改进PPO的雷达抗干扰自适应跳频方法
A Radar Anti-jamming Adaptive Frequency Hopping Method Based on Improved Proximal Policy Optimization(PPO)Algorithm
李家强 1李淑君 1喻庞泽 1陈金立 1姚昌华1
作者信息
- 1. 南京信息工程大学 电子与信息工程学院,南京 210044
- 折叠
摘要
Abstract
In modern electronic warfare,radar systems face increasingly complex jamming challenges.An intelligent anti-jamming decision-making algorithm for frequency-agile radar based on deep reinforcement learning(DRL)is proposed.By integrating DRL with frequency-agile radar technology,an adaptive frequency hopping anti-jamming method is proposed using the proximal policy optimization(PPO)algorithm.First,the interaction between the radar and the jammer is modeled as a partially observable Markov decision process(POMDP),and the reward function is designed based on detection probability.Then,the PPO algorithm is employed,utilizing its clipping mechanism to address the issue of excessive policy updates in traditional policy gradient methods.Finally,multi-layer historical observations are incorporated,and a gated recurrent unit(GRU)is applied to capture long-term dependencies in sequential data,mitigating the information insufficiency in POMDP.Simulation results show that,compared with traditional PPO algorithms,the proposed method improves the detection probability by 8%.关键词
频率捷变雷达/雷达抗干扰/自适应跳频/深度强化学习/近端策略优化(PPO)Key words
frequency-agile radar/radar anti-jamming/adaptive frequency hopping/deep reinforcement learning/proximal policy optimization(PPO)分类
信息技术与安全科学引用本文复制引用
李家强,李淑君,喻庞泽,陈金立,姚昌华..基于改进PPO的雷达抗干扰自适应跳频方法[J].电讯技术,2026,66(9):1456-1463,8.
