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论文:2020,Vol:38,Issue(6):1330-1338 |
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引用本文： |
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谢建峰, 杨啟明, 戴树岭, 王婉扬, 张建东. 基于强化遗传算法的无人机空战机动决策研究[J]. 西北工业大学学报 |
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XIE Jianfeng, YANG Qiming, DAI Shuling, WANG Wanyang, ZHANG Jiandong. Air Combat Maneuver Decision Based on Reinforcement Genetic Algorithm[J]. Northwestern polytechnical university |
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| 基于强化遗传算法的无人机空战机动决策研究 |
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| 谢建峰1,2, 杨啟明3, 戴树岭1, 王婉扬3, 张建东3 |
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1. 北京航空航天大学 自动化科学与电气工程学院, 北京 100191;
2. 中国航空无线电电子研究所, 上海 200241;
3. 西北工业大学 电子信息学院, 陕西 西安 710129 |
| 摘要: |
| 伴随着无人机技术的不断发展，在军事战场上使用无人机的趋势日益明显，但是无人机自主空战能力还有待进一步提高。空战机动决策是实现无人机自主空战的关键。遗传算法拥有较好的鲁棒性和搜索性，适用于大规模优化问题求解，但无法对没有显式目标函数的问题建模。基于强化学习思想，采用改进的强化遗传算法针对无人机的空战机动决策进行建模。根据工程应用需求，建立了典型的仿真测试场景，仿真结果表明基于强化遗传算法建立的空战机动决策模型，能够获得正确的机动决策序列，在作战中获得位置优势。 |
| 关键词:
空战机动决策
遗传算法
强化学习
控制与决策
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| Air Combat Maneuver Decision Based on Reinforcement Genetic Algorithm |
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| XIE Jianfeng1,2, YANG Qiming3, DAI Shuling1, WANG Wanyang3, ZHANG Jiandong3 |
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1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China;
2. China Aeronautical Radio Electronics Research Institute, Shanghai 200241, China;
3. School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China |
| Abstract: |
| With the continuous development of UAV technology, the trend of using UAV in the military battlefield is increasingly obvious, but the autonomous air combat capability of UAV needs to be further improved. The air combat maneuvering decision is the key link to realize the UAV autonomous air combat, and the genetic algorithm has good robustness and global searching ability which is suitable for solving large-scale optimization problems. This paper uses an improved genetic algorithm to model UAV air combat maneuvering decisions. Based on engineering application requirements, a typical simulation test scenario is established. The simulation results show that the air combat maneuvering decision model based on reinforcement genetic algorithm in this paper can obtain the correct maneuvering decision sequence and gain a position advantage in combat. |
| Key words:
air combat maneuvering decision
genetic algorithm
reinforcement learning
control and decision
UAV
model
simulation test scenario
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| 收稿日期: 2020-03-17
修回日期:
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| DOI: 10.1051/jnwpu/20203861330 |
| 基金项目: 航空科学基金（2017ZC53033）资助 |
| 通讯作者:
Email： |
| 作者简介: 谢建峰(1975-),北京航空航天大学博士研究生,主要从事航空电子系统设计、系统建模及仿真验证研究。
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