系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (3): 967-976.doi: 10.12305/j.issn.1001-506X.2022.03.29

• 制导、导航与控制 • 上一篇    下一篇

基于联邦滤波算法的无人机集群分层协同导航

谷旭平*, 唐大全   

  1. 海军航空大学航空作战勤务学院, 山东 烟台 264001
  • 收稿日期:2021-04-15 出版日期:2022-03-01 发布日期:2022-03-10
  • 通讯作者: 谷旭平
  • 作者简介:谷旭平 (1997—), 男, 硕士研究生, 主要研究方向为无人机集群控制与导航|唐大全 (1965—), 男, 教授, 硕士, 主要研究方向为无人机导航与控制

Hierarchical cooperative navigation of UAV swarm based on federated filtering algorithm

Xuping GU*, Daquan TANG   

  1. School of Aviation Operations and Support, Naval Aviation University, Yantai 264001, China
  • Received:2021-04-15 Online:2022-03-01 Published:2022-03-10
  • Contact: Xuping GU

摘要:

为了解决传统单主从式无人机(unmanned aerial vehicle, UAV)相对导航结构因长机故障导致导航精度发散以及全连通协同导航算法计算量和通信负担较重的问题, 提高集群导航稳定性以及导航信息的利用率, 基于联邦滤波算法, 提出了一种分层协同导航算法, 并且根据导航精度将UAV集群分为长机层与僚机层, 建立了UAV集群分层协同导航模型。经过仿真得出, 分层协同导航算法较传统的单主从式协同导航算法具有更好的导航精度; 在一定程度上增加集群中的长机比例, 可以提高集群导航性能; 并且当长机故障时, 具有较好的容错能力和良好的稳定性。

关键词: 无人机集群, 联邦滤波, 导航, 分层协同

Abstract:

In order to solve the problem that the traditional single leader-follower relative navigation structure leads to the divergence of navigation accuracy due to leader failure and the heavy computation and communication burden of the fully connected cooperative navigation algorithm, and improve the stability of swarm navigation and the utilization of navigation information, a hierarchical cooperative navigation algorithm is proposed based on the federal filtering algorithm.The unmanned aerial vehicle (UAV) swarm is divided into two groups according to the navigation accuracy. The UAV swarm hierarchical cooperative navigation model is established in the leader layer and follower layer. The simulation results show that the hierarchical cooperative navigation algorithm has a better navigation accuracy than the traditional single leader-follower cooperative navigation algorithm; to a certain extent, increasing the proportion of the leader in the swarm can improve the navigation performance of the swarm; and when the leader fails, it has better fault tolerance and good stability.

Key words: unmanned aerial vehicle (UAV) swarm, federated filtering, navigation, hierarchical cooperative

中图分类号: