• Electronics Optics & Control
  • Vol. 29, Issue 4, 52 (2022)
ZHU Bakun1, ZHU Weigang2, LI Wei1, YANG Ying1, and GAO Tianhao1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2022.04.011 Cite this Article
    ZHU Bakun, ZHU Weigang, LI Wei, YANG Ying, GAO Tianhao. A Review on Reinforcement Learning Based Radar Jamming Decision-Making Technology[J]. Electronics Optics & Control, 2022, 29(4): 52 Copy Citation Text show less

    Abstract

    The cognitive ability of equipment embodies the fundamental attributes of cognitive electronic warfareand it is also the key to effective jamming on complex and intelligent electronic equipment.As a hot technique in the field of artificial intelligencereinforcement learning has the ability of self-learning not relying on priori datawhich is an important approach to multifunctional radar jamming.Based on the review on traditional algorithms of radar jamming decision-makingas for reinforcement learning based radar jamming decision-makingthe principles and status quo of the technology are analyzedand its performance is verified through simulations.Finallya summary is givenand the outlook for the technology is predicted.
    ZHU Bakun, ZHU Weigang, LI Wei, YANG Ying, GAO Tianhao. A Review on Reinforcement Learning Based Radar Jamming Decision-Making Technology[J]. Electronics Optics & Control, 2022, 29(4): 52
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