系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (1): 89-95.doi: 10.3969/j.issn.1001-506X.2019.01.13

• 系统工程 • 上一篇    下一篇

变权区间数Heronian算子下集群态势觉察一致性评估

高杨, 李东生   

  1. 国防科技大学电子对抗学院, 安徽 合肥 230037
  • 出版日期:2018-12-29 发布日期:2018-12-27

Swarm situation perception consensus evaluation via intervalnumber Heronian operators with variable weights

GAO Yang, LI Dongsheng   

  1. College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China
  • Online:2018-12-29 Published:2018-12-27

摘要:

无人机集群协同态势觉察一致性是集群协同作战获取信息优势的重要条件,基于此提出了基于变权区间数Heronian算子的集群态势觉察一致性评估方法,用于多种(作战仿真)情况下集群协同态势觉察一致性分析。首先,结合集群协同作战需求,从完备性、准确性等方面对一致性评估指标进行建模;然后,考虑多时刻指标数据的不确定性,构建非线性处理的区间决策矩阵,利用变权理论求取权重;最后,考虑指标的关联性,使用区间数加权Heronian平均算子集结指标数据,利用集结的区间数表征集群态势觉察一致性。结果表明,所提指标及方法可以有效分析集群协同态势觉察一致性。

Abstract:

Unmanned aerial vehicle (UAV) swarm cooperative situation perception consensus plays a key role in swarm cooperative combat obtaining information superiority. A consensus evaluation method of swarm cooperative situation perception via intervalnumber Heronian operators with variable weights is given to analyze the situation perception consensus under different combat simulation conditions. Firstly, combined with the pursuits of swarm cooperative engagement, the swarm cooperative situation perception consensus analysis indexes are built from the completeness, correctness, and so on. Then, combined with the uncertainty of multiperiod data, the nonlinear dispose decision matrix and the variable weights are obtained. Finally, combined with the indexes relevance, the index data are aggregated by intervalnumber weighted Heronian mean operators, which could represent the situation perception consensus. The results show that the indexes and method could effectively analyze the swarm cooperative situation perception consensus.