Systems Engineering and Electronics ›› 2020, Vol. 42 ›› Issue (4): 819-825.doi: 10.3969/j.issn.1001-506X.2020.04.12

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DQN based decision-making method of cognitive jamming against multifunctional radar

Bokai ZHANG1,2(), Weigang ZHU1()   

  1. 1. Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China
    2. Department of Graduate Management, Space Engineering University, Beijing 101416, China
  • Received:2019-07-10 Online:2020-03-28 Published:2020-03-28
  • Supported by:
    CEMEE国家重点实验室项目(2018Z0202B)

Abstract:

With the increasing number of tasks that can be performed by multifunctional radar (MFR), the decision-making efficiency of Q-Learning based decision-making methods of cognitive jamming is significantly reduced. Aiming at this, a deep Q neural network (DQN) based jamming decision-making method against MFR is proposed. Firstly, the characteristics of MFR signals are analyzed and the jamming library is constructed. Based on this, the jamming decision-making method is studied. Secondly, through the brief explanation of the DQN principle, the jamming decision-making method and its process are proposed. Finally, the simulation test of the decision-making method is carried out and the necessity of the method is verified by comparing the decision-making performance of DQN and Q-Learning. In order to improve the real-time and accuracy of decision-making, the DQN algorithm has been improved. On this basis, combined with prior knowledge, the decision-making efficiency is further improved. The simulation test shows that the decision-making method can learn the jamming effect in the actual battlefield autonomously, and complete the decision-making of cognitive jamming against the MFR that can perform multiple radar tasks.

Key words: multifunctional radar (MFR), jamming decision-making, deep Q neural network (DQN), cognitive electronic warfare, priori knowledge

CLC Number: 

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