An Electronic Jamming Method Based on a Distributed Information Sharing Mechanism

被引:3
作者
Zhang, Pan [1 ,2 ]
Huang, Yi [1 ,2 ]
Jin, Zhonghe [1 ,2 ]
机构
[1] Zhejiang Univ, Microsatellite Res Ctr, Hangzhou 310027, Peoples R China
[2] Zhejiang Univ, Zhejiang Microsatellite Res Key Lab, Hangzhou 310027, Peoples R China
关键词
information sharing; multi-agent electronic jammer; Q-learning; situational awareness; CONTAINMENT CONTROL; MULTIAGENT SYSTEMS; ALLOCATION; POWER;
D O I
10.3390/electronics12092130
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In an electronic jamming system, the ability to adequately perceive information determines the effectiveness of an electronic countermeasures strategy. This paper proposes a new method based on the combination of a multi-agent electronic jammer and an information sharing mechanism. With the development of intelligent technology and deep learning, these technologies have been applied in electronic countermeasure game systems. Introducing intelligent technology into the electronic confrontation system can greatly improve decision-making efficiency. At the same time, a multi-agent electronic countermeasure cooperative system based on the information sharing method can break through the limited information perception capabilities of a single agent, thereby greatly improving the survivability of jamming systems in electronic warfare. Experimental results show that our method requires a lower jamming-to-signal ratio than the single jammer method to achieve effective electronic jamming. In addition, the electronic jamming parameters can be updated automatically as the external electromagnetic environment changes quickly, realizing a more intelligent electronic jamming system.
引用
收藏
页数:18
相关论文
共 22 条
  • [1] Distributed Operation of Wind Farm for Maximizing Output Power: A Multi-Agent Deep Reinforcement Learning Approach
    Bui, Van-Hai
    Nguyen, Thai-Thanh
    Kim, Hak-Man
    [J]. IEEE ACCESS, 2020, 8 : 173136 - 173146
  • [2] fbo, DARPA BEH LEARN AD E
  • [3] A fast efficient power allocation algorithm for target localization in cognitive distributed multiple radar systems
    Feng, Han-Zhe
    Liu, Hong-Wei
    Yan, Jun-Kun
    Dai, Feng-Zhou
    Fang, Ming
    [J]. SIGNAL PROCESSING, 2016, 127 : 100 - 116
  • [4] Distributed Robust Global Containment Control of Second-Order Multiagent Systems With Input Saturation
    Fu, Junjie
    Wan, Ying
    Wen, Guanghui
    Huang, Tingwen
    [J]. IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2019, 6 (04): : 1426 - 1437
  • [5] Ground threat evaluation and jamming allocation model with Markov chain for aircraft
    Han, Lu
    Ning, Qian
    Chen, Bingcai
    Lei, Yinjie
    Zhou, Xinzhi
    [J]. IET RADAR SONAR AND NAVIGATION, 2020, 14 (07) : 1039 - 1045
  • [6] He J.-H., 2017, FPGA SOFTWARE DESIGN
  • [7] Kingsley N, 2014, IEEE RAD CONF, P1329, DOI 10.1109/RADAR.2014.6875805
  • [8] Distributed containment control of multi-agent systems with general linear dynamics in the presence of multiple leaders
    Li, Zhongkui
    Ren, Wei
    Liu, Xiangdong
    Fu, Mengyin
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2013, 23 (05) : 534 - 547
  • [9] Threat evaluation and jamming allocation
    Osner, Nicholas R.
    du Plessis, Warren P.
    [J]. IET RADAR SONAR AND NAVIGATION, 2017, 11 (03) : 459 - 465
  • [10] Electronic warfare in the optical band: Main features, examples and selected measurement data
    Ostrowski, Roman
    Cywinsli, Artur
    Strzelec, Marek
    [J]. DEFENCE TECHNOLOGY, 2021, 17 (05) : 1636 - 1649