文章摘要
饶宁,许华,宋佰霖.融合动作剔除的深度竞争双Q网络智能干扰决策算法[J].空军工程大学学报:自然科学版,2021,22(4):92-98
融合动作剔除的深度竞争双Q网络智能干扰决策算法
An Intelligent Jamming Decision Algorithm Based on Action Elimination Dueling Double Deep Q Network
  
DOI:
中文关键词: 干扰决策  深度双Q网络  竞争网络  干扰动作剔除
英文关键词: jamming decision making  double deep Q network  dueling network  jamming action elimination
基金项目:
作者单位
饶宁,许华,宋佰霖 空军工程大学信息与导航学院西安710077 
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中文摘要:
      为解决战场通信干扰决策问题,设计了一种融合动作剔除的深度竞争双Q网络智能干扰决策方法。该方法在深度双Q网络框架基础上采用竞争结构的神经网络决策最优干扰动作,并结合优势函数判断各干扰动作的相对优劣,在此基础上引入无效干扰动作剔除机制加快学习最佳干扰策略。当面对未知的通信抗干扰策略时,该方法能学习到较优的干扰策略。仿真结果表明,当敌方通信策略发生变化时,该方法能自适应调整干扰策略,稳健性较强,和已有方法相比可达到更高的干扰成功率,获得更大的干扰效能。
英文摘要:
      In view of the problem of intelligent jamming decision making in battlefield communication, an action elimination dueling double deep Q network intelligent jamming decision algorithm is designed. Based on the framework of double deep Q network, this algorithm utilizes a neural network with a dueling structure for determining the optimal jamming action in combination with the advantage function to judge the relative pros and cons of each jamming action. And then on the basis of the above mentioned, an invalid jamming action elimination mechanism is introduced to speed up the learning of the best jamming strategy. The method can learn a better jamming strategy in the face of an unknown communication anti jamming strategy. The simulation results show that when the enemy changes communication strategy, the method can adaptively adjust the jamming strategy and have stronger robustness. Compared with the existing methods, this method can achieve a higher jamming success rate with greater jamming efficacy.
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