一个基于地面的视觉系统用于无人机检测和高度测量,以及在边缘设备上部署和评估幽灵-YOLOv11n
Hongyu Wang1, Yifeng Qu1, Zheng Dang1
1School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China.
Sensors (Basel, Switzerland)
|January 10, 2026
概括
本研究介绍了一种用于反无人机应用的轻量级无人机探测和高度测量系统. 幽灵-YOLOv11n模型在边缘设备上实现了高精度和实时性能,使得有效的地面监控成为可能.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 航空航天工程 航空航天工程
背景情况:
- 未经授权的无人机对关键基础设施的威胁越来越大.
- 需要有效的地面对空监视系统.
- 现有的无人机检测方法的局限性.
研究的目的:
- 从地面角度开发一个轻量化框架,用于无人机探测和高度测量.
- 使用增强的YOLOv11n模型优化无人机检测.
- 提供一个具有成本效益的,边缘部署的反无人机解决方案.
主要方法:
- 介绍了Ghost-YOLOv11n,将GhostConv模块集成到YOLOv11n中,以减少复杂性.
- 在LuBanCat4边缘设备上部署,具有Rockchip RK3588S NPU加速.
- 使用具有单眼范围的扩展卡尔曼波器进行高度估计.
主要成果:
- 幽灵YOLOv11n在一个8795图像数据集上实现了98.8%的mAP0.5.
- 该系统在边缘设备上展示了20 FPS的性能.
- 在地面监测场景中,高度测量误差为10%至30米.
结论:
- 拟议的框架为地面无人机监视提供了一种高效和轻量级的解决方案.
- 幽灵-YOLOv11n提供了一个计算高效和准确的物体探测器.
- 该系统适用于实时,边缘部署的反无人机应用.
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