电子器件2024，Vol.47Issue(2)：544-551,8.DOI:10.3969/j.issn.1005-9490.2024.02.038
基于多智能体强化学习的目标跟踪辐射方法及设计
Target Tracking Radiation Method and Design Based on Multi-Agent Reinforcement Learning
摘要
Abstract
Aiming at the problem that single-platform microwave transmitting devices have maximum transmit power limitations in dis-tributed spatial power synthesis,a path planning method of microwave transmitting devices based on Friend-Q multi-intelligent reinforce-ment learning is proposed to achieve the radiation intensity of 10 mW/cm2～15 mW/cm2 lasting 4 min or more to the target.The rela-tionship between exploration and utilization is balanced by the variable ε-greedy strategy,and a selective input power scheme is pro-posed to reduce the energy consumption of the system.Through the training of three representative simulation scenarios,the experimental results show that compared with the scattered remote scene and single proximity scene,the success rate of path combined scene is increased by 55.7%and 120.9%,respectively,which confirms that the reasonable location arrangement of microwave radiation sources can greatly improve the success rate of the model.Compared with the model using stochastic strategy,the success rates of the model trained by multi-agent reinforcement learning in three simulation scenes are increased by 48.8%,72%and 41.8%,respectively,which further verifies the effectiveness of the algorithm.关键词
多智能体强化学习/分布式空间功率合成/跟踪辐射/路径规划Key words
multi-agent reinforcement learning/distributed space power synthesis/tracking radiation/path planning分类
信息技术与安全科学引用本文复制引用
陈翰,张远媛,何聪,朱城磊,张为..基于多智能体强化学习的目标跟踪辐射方法及设计[J].电子器件,2024,47(2):544-551,8.基金项目
2021年国防科技创新特区项目 （）
