Issue |
JNWPU
Volume 38, Number 6, December 2020
|
|
---|---|---|
Page(s) | 1330 - 1338 | |
DOI | https://doi.org/10.1051/jnwpu/20203861330 | |
Published online | 02 February 2021 |
Air Combat Maneuver Decision Based on Reinforcement Genetic Algorithm
基于强化遗传算法的无人机空战机动决策研究
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
Received:
17
March
2020
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.
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。
Key words: air combat maneuvering decision / genetic algorithm / reinforcement learning / control and decision / UAV / model / simulation test scenario
关键字 : 空战机动决策 / 遗传算法 / 强化学习 / 控制与决策
© 2020 Journal of Northwestern Polytechnical University. All rights reserved.
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