对抗智能干扰的主动防御技术

冯智斌; 徐煜华; 杜智勇; 刘鑫; 李文; 韩昊; 张晓博

doi:10.11959/j.issn.1000-436x.2022198

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对抗智能干扰的主动防御技术

学术论文 | 更新时间：2024-06-05

- 对抗智能干扰的主动防御技术
- Active defense technology against intelligent jammer
- 通信学报 2022年43卷第10期页码：42-54
- 作者机构：
  
  1. 陆军工程大学通信与工程学院，江苏南京 210014
  2. 国防科技大学信息通信学院，湖北武汉 430010
  3. 桂林理工大学信息科学与工程学院，广西桂林 541006
- 作者简介：
  
  [ "冯智斌（1995− ），男，河南平顶山人，陆军工程大学博士生，主要研究方向为智能抗干扰、博弈论和智能干扰" ]
  [ "徐煜华（1983− ），男，贵州毕节人，博士，陆军工程大学教授、博士生导师，主要研究方向为认知无线电、智能频谱对抗、无人机集群通信和博弈论" ]
  [ "杜智勇（1986− ），男，湖北武汉人，博士，国防科技大学副教授，主要研究方向为无线通信中的智能决策、智能抗干扰和无人机通信" ]
  [ "刘鑫（1983− ），男，江西上饶人，博士，桂林理工大学副教授、硕士生导师，主要研究方向为智能抗干扰、深度强化学习和软件无线电" ]
  [ "李文（1996− ），男，江西新余人，陆军工程大学博士生，主要研究方向为博弈论、机器学习和智能抗干扰" ]
  [ "韩昊（1996− ），男，山东临沂人，陆军工程大学博士生，主要研究方向为智能频谱对抗、博弈论和机器学习" ]
  [ "张晓博（1983− ），男，河南南阳人，博士，陆军工程大学讲师，主要研究方向为无线网络安全、智能抗干扰和博弈论" ]
- 基金信息：
  
  国家自然科学基金资助项目(62071488);国家自然科学基金资助项目(61961010)
- DOI：10.11959/j.issn.1000-436x.2022198
  中图分类号： TN975
- 网络出版日期：2022-10，
  
  纸质出版日期：2022-10-25
- 稿件说明：
移动端阅览
冯智斌, 徐煜华, 杜智勇, 等. 对抗智能干扰的主动防御技术[J]. 通信学报, 2022,43(10):42-54.

Zhibin FENG, Yuhua XU, Zhiyong DU, et al. Active defense technology against intelligent jammer[J]. Journal on communications, 2022, 43(10): 42-54.
冯智斌, 徐煜华, 杜智勇, 等. 对抗智能干扰的主动防御技术[J]. 通信学报, 2022,43(10):42-54. DOI： 10.11959/j.issn.1000-436x.2022198.

Zhibin FENG, Yuhua XU, Zhiyong DU, et al. Active defense technology against intelligent jammer[J]. Journal on communications, 2022, 43(10): 42-54. DOI： 10.11959/j.issn.1000-436x.2022198.

摘要

摘要：在复杂电磁对抗环境下，干扰的智能化发展给无线通信造成了严重威胁，而传统抗干扰方法往往都是被动地调整工作模式或参数，在面对智能干扰时处于劣势甚至被压制。针对此问题，提出了干扰主动防御技术体系架构，旨在通过主动调整己方的通信行为，扰乱干扰的学习过程并降低干扰效能。为了渐进达到“理解对手”“克制对手”“战胜对手”的目的，在博弈论和对抗机器学习理论方法指导下，围绕干扰反向推理、算法脆弱性分析和对抗策略设计、抗干扰策略自主优化和在线决策3个方面对关键技术展开论述。最后，结合2个具体案例，验证了所提技术架构的可行性和有效性。

Abstract

In the complex electromagnetic countermeasure environment

the intelligent development of jammer has caused a serious threat to wireless communication

while the traditional anti-jamming methods often passively adjusted the working mode or parameters

which will be at a disadvantage or even suppressed in the face of intelligent jammer.To solve this problem

a technical framework of active defense against jammer was proposed

aiming to disrupt the learning process of the intelligent jammer and reduce the jamming efficacy.In order to gradually achieve the goals of “understanding opponent”“controlling opponent” and “defeating opponent”

under the guidance of game theory and adversarial machine learning

the key technologies were discussed from three aspects: backward reasoning of jammer

algorithm vulnerability analysis and confrontational strategy design

independent optimization and online decision-making of anti-jamming strategy.Finally

combined with two specific cases

the feasibility and effectiveness of the proposed technical framework were verified.

关键词

Keywords

references

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