上海交通大学学报(自然版) ›› 2014, Vol. 48 ›› Issue (07): 907-913.

• 无线电电子学、电信技术 • 上一篇    下一篇

多无人机模糊态势的分布式协同空战决策

陈侠,魏晓明,徐光延
  

  1. (沈阳航空航天大学 自动化学院, 沈阳 110136)
     
     
  • 收稿日期:2013-12-06 出版日期:2014-07-28 发布日期:2014-07-28
  • 基金资助:

    国家自然科学基金(61074159),辽宁省自然科学基金(20092053)资助项目

Multiple Unmanned Aerial Vehicle Decentralized Cooperative Air Combat Decision Making with Fuzzy Situation

CHEN Xia,WEI Xiaoming,XU Guangyan
  

  1. (School of Automation, Shenyang Aerospace University, Shenyang 110136, China)
  • Received:2013-12-06 Online:2014-07-28 Published:2014-07-28

摘要:

针对不确定环境下的多无人机协同攻击多目标的空战问题给出了一种分析方法. 首先通过分析不确定环境下的无人机空战态势,建立了多无人机模糊态势的任务分配模型. 然后提出了异步一致性拍卖算法,将目标收益作为竞标的依据,给出了不确定环境下的多无人机协同攻击多目标的分布式空战决策方法.仿真结果表明,该算法在双方机群较大时能够实现快速收敛,提高了空战效率与资源利用率,且具有良好的稳定性和可扩展性.

 

关键词: 模糊理论, 异步一致性拍卖算法, 协同空战, 分布式任务分配

Abstract:

This paper presented an analytical method for multiple UAV(unmanned aerial vehicle) cooperatively attacking multiple targets in an uncertain environment. Firstly, the air combat situation under uncertain environment was analyzed, and the Task allocation model was established. Then the ACBAA(asynchronous consensusbased auction algorithm) algorithm was improved, the gains of the targets was considered as a basis for bids, and the method of aircombat decisionmaking for multiple UAV cooperatively attacking multiple targets in uncertain environment was proposed. Simulation results show that the algorithm converges quickly when the size of both sides is large, improves the combat efficiency and resource utilization, and is better in stability and scalability.
 

Key words: fuzzy theory, asynchronous consensusbased auction algorithm (ACBAA), cooperative air combat, decentralized task allocation

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