Active defense technology against intelligent jammer

Zhibin FENG; Yuhua XU; Zhiyong DU; Xin LIU; Wen LI; Hao HAN; Xiaobo ZHANG

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

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Active defense technology against intelligent jammer

Papers | 更新时间：2024-06-05

- Active defense technology against intelligent jammer
- Journal on Communications Vol. 43, Issue 10, Pages: 42-54(2022)
- 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：
- 基金信息：
  
  The National Natural Science Foundation of China(62071488);The National Natural Science Foundation of China(61961010)
- DOI：10.11959/j.issn.1000-436x.2022198
  CLC： TN975
- Online First：2022-10，
  
  Published：25 October 2022
- 稿件说明：
移动端阅览
Zhibin FENG, Yuhua XU, Zhiyong DU, et al. Active defense technology against intelligent jammer[J]. Journal on Communications, 2022, 43(10): 42-54.
DOI：

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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