基于联邦滤波算法的无人机集群分层协同导航

doi:10.12305/j.issn.1001-506X.2022.03.29

Abstract

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

CLC Number:

V249

Xuping GU, Daquan TANG. Hierarchical cooperative navigation of UAV swarm based on federated filtering algorithm[J]. Systems Engineering and Electronics, 2022, 44(3): 967-976.

Figures/Tables 12

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References 33

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参数	数值
加速度计白噪声均方根/μg₀	100
加速度计一阶马尔可夫噪声均方根/((°)·h^-1)	100
加速度计一阶马尔可夫时间常数/s	3 600
陀螺仪白噪声均方根/((°)·h^-1)	0.1
陀螺仪一阶马尔可夫噪声均方根/((°)·h^-1)	0.1
陀螺仪一阶马尔可夫时间常数/s	3 600
相对速度测量白噪声均方根/(m·s^-1)	1
相对距离测量白噪声均方根/m	3
仰角测量白噪声均方根/(°)	0.1
方位角测量白噪声均方根/(°)	0.1

算法	时间
FF	1.721
KF	4.346
PF	4.074

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Hierarchical cooperative navigation of UAV swarm based on federated filtering algorithm

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