多无人机磁测中用视觉协同定位，实现厘米级单轴精度。
A Visual Cooperative Localization Method for Airborne Magnetic Surveying Based on a Manifold Sensor Fusion Algorithm Using Lie Groups
- 基于李群的流形融合算法，结合视觉信息提升定位精度。
- 实飞测试显示单轴达厘米级，三维整体达分米级精度。
- 适合在无GPS信号的复杂环境进行高精度磁测任务。
近年来，无人机技术的发展推动了多无人机航空磁测系统在GNSS信号受阻或干扰的密闭环境中的应用。本文聚焦于航空磁测场景，为获取反映地磁场的真实磁测数据，磁传感器需远离其他电子设备，导致定位难题。为此，提出一种基于视觉的协同定位解决方案，包含视觉处理模块和改进的基于流形的传感器融合算法，实现了可靠且精确的位置信息。真实飞行实验验证了该方法的有效性，结果显示单轴精度达到厘米级，三维整体定位精度达分米级。
原文摘要 · Abstract (English)
Recent advancements in UAV technology have spurred interest in developing multi-UAV aerial surveying systems for use in confined environments where GNSS signals are blocked or jammed. This paper focuses airborne magnetic surveying scenarios. To obtain clean magnetic measurements reflecting the Earth's magnetic field, the magnetic sensor must be isolated from other electronic devices, creating a significant localization challenge. We propose a visual cooperative localization solution. The solution incorporates a visual processing module and an improved manifold-based sensor fusion algorithm, delivering reliable and accurate positioning information. Real flight experiments validate the approach, demonstrating single-axis centimeter-level accuracy and decimeter-level overall 3D positioning accuracy.
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