基于情景分析的航空集群决策规则库构建方法

doi:10.7527/S1000-6893.2019.23737

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基于情景分析的航空集群决策规则库构建方法

胡利平^1,2, 梁晓龙^1,2, 何吕龙^1,2, 张佳强^1,2, 任宝祥¹, 齐铎^1,2

1. 空军工程大学空管领航学院航空集群技术与作战运用实验室, 西安 710051;
2. 空军工程大学空管领航学院国家空管防相撞技术重点实验室, 西安 710051

收稿日期:2019-12-13 修回日期:2019-12-17 出版日期:2020-06-30 发布日期:2019-12-26
通讯作者: 胡利平 E-mail:452367076@qq.com
基金资助:
国家自然科学基金（61703427）；国防创新特区项目

Construction method of aviation swarm decision rule base based on scenario analysis

HU Liping^1,2, LIANG Xiaolong^1,2, HE Lyulong^1,2, ZHANG Jiaqiong^1,2, REN Baoxiang¹, QI Duo^1,2

1. Aviation Swarm Technology and Operational Application Laboratory, Air Traffic Control and Navigation College, Air Force Engineering University, Xi'an 710051, China;
2. National Key Laboratory of Air Traffic Collision Prevention, Air Traffic Control and Navigation College, Air Force Engineering University, Xi'an 710051, China

Received:2019-12-13 Revised:2019-12-17 Online:2020-06-30 Published:2019-12-26
Supported by:
National Natural Science Foundation of China (61703427); China National Defense Innovation Special Zone Project

摘要/Abstract

摘要： 针对传统的规则学习算法很难解决顶层决策，以及现阶段航空集群作为一种新兴的作战样式，没有太多现成的数据和案例可供参考，暂不具备"从战争中学习战争"条件等难题，从战争设计的角度出发，探讨性地提出了一种基于情景分析的规则库构建方法。首先，从系统演化的外部触发条件和内部驱动机制出发，提出了基于事件触发-规则驱动的自主决策机制；然后，将航空集群决策规则拆分为事件、条件、动作3部分，并采用事件-条件-动作（ECA）描述机制进行规范化表达；最后，借鉴情景分析理论的思想，通过详细分析作战过程的逻辑关系、状态变迁，实现对象、事件、行为的关联，并以无人机自主察打任务规则提取为例进行了验证分析。

关键词: 航空集群, 情景分析, 自主决策, 规则提取, 决策规则库, 事件触发-规则驱动

Abstract: The traditional algorithm of rule learning is difficult to solve the problem of top-level decision-making. In addition, as a new type of combat, aviation swarm does not have sufficient labeled data and battle cases for reference at this stage, thus the condition for ‘learn to fight from the war’ is temporarily immature. To solve the above problems, this paper proposes a construction method of rule base based on the scenario analysis from the perspective of war design. Firstly, based on the external triggering conditions and internal driving mechanism of system evolution, an event-triggered and rule-driven autonomous decision-making mechanism is proposed. Secondly, the decision rules of aviation swarm are divided into event, condition and action and are expressed by the Event-Condition-Action (ECA) description mechanism. Finally, by adopting the idea of scenario analysis theory, the logic and state transition of the operational process are analyzed in detail, and the associations among objects, events, and behaviors are finally realized. Moreover, the rules extraction of autonomous reconnaissance and strike mission using UAV swarm is carried out to verify the proposed theory.

Key words: aviation swarm, scenario analysis, autonomous decision making, rule extraction, decision rule base, event-triggered and rule-driven

中图分类号:

V219

胡利平, 梁晓龙, 何吕龙, 张佳强, 任宝祥, 齐铎. 基于情景分析的航空集群决策规则库构建方法[J]. 航空学报, 2020, 41(S1): 723737-723737.

HU Liping, LIANG Xiaolong, HE Lyulong, ZHANG Jiaqiong, REN Baoxiang, QI Duo. Construction method of aviation swarm decision rule base based on scenario analysis[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(S1): 723737-723737.

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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于情景分析的航空集群决策规则库构建方法

Construction method of aviation swarm decision rule base based on scenario analysis

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