基于视觉协同的蜂群自主导航技术

doi:10.12305/j.issn.1001-506X.2026.04.28

Abstract

Abstract:

Aiming at the problem of greatly reduced accuracy and reliability of unmanned aerial vehicle （UAV） swarm navigation under satellite navigation denial conditions, a cooperative navigation algorithm based on vision and data chain ranging is proposed. Firstly, a swarm autonomous navigation model based on visual cooperation is established, and a distributed cooperative navigation algorithm based on maximum correntropy criterion Kalman filter （MCC-KF） is designed, which improves the cooperative navigation and positioning accuracy under non-Gaussian noise. Then, a delay compensation strategy and algorithm are proposed for the delay problems occurring in the image processing process and data transmission process. Finally, simulation shows that the navigation accuracy of UAV swarm in satellite denial environment is significantly improved by using distributed cooperative navigation and delay compensation strategy.

Key words: unmanned aerial vehicle (UAV) swarm, autonomous navigation, delay compensation, maximum correntropy criterion Kalman filter

CLC Number:

V 249.3

Zhi YANG, Feng YU, Siying LIN, Zijun ZHOU. Swarm autonomous navigation technology based on visual collaboration[J]. Systems Engineering and Electronics, 2026, 48(4): 1396-1403.

Figures/Tables 11

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References 33

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无人机类型	传感器	参数	数值
所有无人机	航姿系统	俯仰角误差/（°）	0.2（RMS）
		滚转角误差/（°）	0.2（RMS）
		偏航角误差/（°）	1（RMS）
	加速度计	零偏误差/g	1.6×10⁻⁵
	加速度计	一阶马尔可夫相关时间/s	1800
	数据链	测距噪声/m 通信方式	30 轮询通信
	相机	测角误差/（°）视场宽度/（°）	1 120
锚节点	GNSS	位置误差/m	10
锚节点	GNSS	速度误差/（m/s）	0.2

情况	经度误差	纬度误差	高度误差
无修正	259.98	170.87	4.54
有修正	12.88	8.27	2.96

滤波方式	经度误差	纬度误差	高度误差
EKF	17.61	14.47	5.79
MCC-KF	12.88	8.27	2.96

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Swarm autonomous navigation technology based on visual collaboration

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