无线电通信技术2025，Vol.51Issue(2)：262-273,12.DOI:10.3969/j.issn.1003-3114.2025.02.006
基于动态频率集的无人集群智能选频抗干扰算法
Intelligent Frequency Selection Anti-jamming Algorithm for UAV Swarms Based on Dynamic Frequency Sets
摘要
Abstract
Cognitive frequency hopping is a key technology for improving the robustness of unmanned cluster communication links in complex electromagnetic environments.However,inaccurate perception results and unreliable feedback information can lead to per-formance degradation in unmanned cluster cognitive frequency hopping communication.In response to the above issues,with the opti-mization goal of improving long-term successful transmission rate and reducing hopping overhead,this paper proposes an intelligent hopping algorithm based on reinforcement learning.The algorithm uses time-frequency resource blocks as the basic learning unit,and dynamically decides the optimal frequency point for each time slot in the time-frequency resource block by learning the transmission re-sults and interference rules in a distributed manner.On this basis,a hierarchical clustering network architecture is introduced,which dynamically adjusts the hopping frequency set based on time frames through centralized aggregation,decision-making,and distribution of unmanned cluster head nodes,reducing network hopping overhead and supporting large-scale unmanned cluster networks.The simu-lation results show that the proposed algorithm achieves a high long-term transmission success rate in malicious interference environ-ments where perception results and feedback information are unreliable,and the algorithm reduces hopping overhead while achieving maximum anti-interference performance through dynamic frequency set adjustment.关键词
无人集群/智能选频/强化学习/抗干扰/动态频率集Key words
unmanned swarm/intelligent frequency selection/reinforcement learning/anti-jamming/dynamic frequency set分类
信息技术与安全科学引用本文复制引用
刘杰,胡晨骏,时荔蕙,辜方林,赵海涛..基于动态频率集的无人集群智能选频抗干扰算法[J].无线电通信技术,2025,51(2):262-273,12.基金项目
国家自然科学基金重点基金(91331020) （91331020）
自然科学基金重大研究计划(92367302) Key Fund of National Natural Science Foundation of China(91331020) （92367302）
National Natural Science Foundation Major Research Plan(92367302) （92367302）
