导航

ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2020, Vol. 41 ›› Issue (S1): 723737-723737.doi: 10.7527/S1000-6893.2019.23737

Previous Articles     Next Articles

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

HU Liping1,2, LIANG Xiaolong1,2, HE Lyulong1,2, ZHANG Jiaqiong1,2, REN Baoxiang1, QI Duo1,2   

  1. 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

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

CLC Number: