自主空战机动决策技术研究进展与展望
在强对抗、高动态的现代空战环境中,以空战决策为核心的自主空战在减轻飞行员决策压力、提高决策效率和准确性、提升无人机作战效能、实现有人/无人协同、探索新战术战法等方面发挥着重要作用.首先,本文分析了视距内空战和超视距空战在现代空战中的地位和关系,给出了自主空战机动决策的定义,并阐述了其在空战中的实际意义.其次,分析了自主空战机动决策在现代空战发展中的重要作用.然后,将现有自主空战机动决策建模与求解方法分为基于博弈论的方法、基于优化理论的方法和基于数据驱动的方法3大类,并系统地梳理总结了各类方法的研究分支、特点、优势及缺陷.进一步地,以1v1空战为对抗场景并选取代表算法,直观对比了3类方法的特点和...
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| Published in | 控制理论与应用 Vol. 40; no. 12; pp. 2104 - 2129 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
国防科技大学智能科学学院,长沙湖南 410073
01.12.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-8152 |
| DOI | 10.7641/CTA.2023.30210 |
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| Abstract | 在强对抗、高动态的现代空战环境中,以空战决策为核心的自主空战在减轻飞行员决策压力、提高决策效率和准确性、提升无人机作战效能、实现有人/无人协同、探索新战术战法等方面发挥着重要作用.首先,本文分析了视距内空战和超视距空战在现代空战中的地位和关系,给出了自主空战机动决策的定义,并阐述了其在空战中的实际意义.其次,分析了自主空战机动决策在现代空战发展中的重要作用.然后,将现有自主空战机动决策建模与求解方法分为基于博弈论的方法、基于优化理论的方法和基于数据驱动的方法3大类,并系统地梳理总结了各类方法的研究分支、特点、优势及缺陷.进一步地,以1v1空战为对抗场景并选取代表算法,直观对比了3类方法的特点和性能差异.最后,针对当前自主空战机动决策技术的痛点问题提出了未来研究和发展的方向. |
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| AbstractList | 在强对抗、高动态的现代空战环境中,以空战决策为核心的自主空战在减轻飞行员决策压力、提高决策效率和准确性、提升无人机作战效能、实现有人/无人协同、探索新战术战法等方面发挥着重要作用.首先,本文分析了视距内空战和超视距空战在现代空战中的地位和关系,给出了自主空战机动决策的定义,并阐述了其在空战中的实际意义.其次,分析了自主空战机动决策在现代空战发展中的重要作用.然后,将现有自主空战机动决策建模与求解方法分为基于博弈论的方法、基于优化理论的方法和基于数据驱动的方法3大类,并系统地梳理总结了各类方法的研究分支、特点、优势及缺陷.进一步地,以1v1空战为对抗场景并选取代表算法,直观对比了3类方法的特点和性能差异.最后,针对当前自主空战机动决策技术的痛点问题提出了未来研究和发展的方向. |
| Abstract_FL | In the realm of modern air combat,characterized by intense confrontation and high dynamics,autonomous air combat plays a crucial role.It can alleviate the decision-making pressure on pilots,enhance decision-making efficiency and accuracy,improve the effectiveness of unmanned aerial vehicles,facilitate manned and unmanned coordination,and explore new tactics.This paper begins by analyzing the status and interrelationships of within visual range and beyond visual range air combat.We provide a definition of maneuver decisions and highlighting their significance in modern air combat.Next,the importance of autonomous air combat maneuver decisions in the advancement of modern air combat is thoroughly analyzed.Then,existing modeling frameworks and solving methods of autonomous air combat maneuver decisions are reviewed.These methods are categorized into game theory-based,optimization theory-based,and data-driven methods.Each category is thoroughly summarized,including research branches,characteristics,advantages,and limitations.Furthermore,taking the 1v1 air combat as the confrontation scenario and selecting representative algorithms,the performance differences of the three category methods are compared intuitively.Finally,taking into account the core issues,we present several directions for future research and development. |
| Author | 刘权 黄健 陈浩 周思航 张中杰 |
| AuthorAffiliation | 国防科技大学智能科学学院,长沙湖南 410073 |
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| Author_FL | CHEN Hao LIU Quan ZHOU Si-hang HUANG Jian ZHANG Zhong-jie |
| Author_FL_xml | – sequence: 1 fullname: CHEN Hao – sequence: 2 fullname: HUANG Jian – sequence: 3 fullname: LIU Quan – sequence: 4 fullname: ZHOU Si-hang – sequence: 5 fullname: ZHANG Zhong-jie |
| Author_xml | – sequence: 1 fullname: 陈浩 – sequence: 2 fullname: 黄健 – sequence: 3 fullname: 刘权 – sequence: 4 fullname: 周思航 – sequence: 5 fullname: 张中杰 |
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| Keywords | 数据驱动 autonomous air combat 博弈论 优化理论 games 强化学习 maneuver decision data driven 自主空战 机动决策 optimization theory reinforcement learning |
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