系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (11): 2633-2640.doi: 10.3969/j.issn.1001-506X.2019.11.29

• 通信与网络 • 上一篇    下一篇

蜂群无人机系统的网络鲁棒性设计

陈旿1,2, 范铭楷1, 李泽宏1, 金鑫1, 洪亮1   

  1. 1. 西北工业大学自动化学院, 陕西 西安 710129;
    (2. 通信网信息传输与分发技术国家重点实验室, 河北 石家庄 050081
  • 出版日期:2019-10-30 发布日期:2019-11-05

Design of network robustness for drone swarm system

CHEN Wu1,2, FAN Mingkai1, LI Zehong1, JIN Xin1, HONG Liang1   

  1. 1. School of Automation, Northwestern Polytechnical University, Xi’an 710129, China;
    (2. Science and Technology on Communication Networks Laboratory, Shijiazhuang 050081, China
  • Online:2019-10-30 Published:2019-11-05

摘要: 针对蜂群无人机系统作战周期短、链路质量快速变化的特点,引入灰预测方法,提出了一种小样本条件下的链路快速评估算法。在此基础上,实现对节点的度分布进行快速估算,为蜂群无人机系统网络鲁棒性控制提供数据基础。然后将平均一致性方法与渗流理论中的MOLLY-REED准则相结合,克服了MOLLY-REED准则需要全网泛洪及不适合应用于蜂群无人机系统的缺点。最后通过配置节点的度分布,建立对节点损失具有高鲁棒性的网络拓扑结构。仿真结果表明,所提出的方法可有效提高蜂群无人机系统的通信网络对节点损失的鲁棒性。

关键词: 蜂群无人机, 一致性, 渗流, MOLLY-REED准则, 鲁棒性, 灰预测

Abstract: Aiming at the characteristics that the short battle cycle and link quality’s quick change of the drone swarm system, a fast link evaluation algorithm under the condition of small samples is proposed by introducing the gray prediction method. On this basis, the quick estimation of nodes’ degree distribution is achieved, which provides data basis for network robustness control of the drone swarm system. Then the average consistency method is combined with the MOLLY-REED criterion in the percolation theory to overcome the disadvantage that the MOLLY-REED criterion needs the whole network’s flooding and is not suitable for the application of the drone swarm system. By configuring the degree distribution of nodes, a network topology with high robustness to node loss is established. The simulation results show that the proposed method can effectively improve the robustness of the drone swarm system’s communication network to node loss.

Key words: drone swarm, consensus, percolation, MOLLY-REED criterion, robustness, gray prediction