Scholarlink

<p>In response to the demand for lightweight drone target detection in the field of drone countermeasures, a portable drone intelligent detection system based on YOLOv11 is proposed in this study. The system consists of a drone detection module, a data transmission module, and a main station, with the aim of achieving precise drone detection, real-time localization, and data transmission. The core component of the system is the drone detection module, which includes four hardware units: a USB camera, a LubanCat4 development board, a GPS, and a 4G module. It is capable of performing image capture, drone target detection, target height measurement, and real-time positioning. The specific workflow is as follows: images are captured by the USB camera and transmitted to the LubanCat4 development board, where the YOLOv11 algorithm is applied for drone target detection, and information such as the target’s bounding box position and confidence level is output. Based on the target’s bounding box width, camera focal length, pixel size, and other data, the drone’s flight height is measured using the similar triangle method. Real-time positioning data, including latitude and longitude, is provided by the GPS and sent to the development board. Finally, the EC20 4G module is used to upload the drone detection information and GPS positioning data to the main station, enabling remote data transmission. The system offers efficient and accurate drone detection and real-time data transmission capabilities, making it suitable for various drone monitoring applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Portable Drone Detection with Optimized YOLOv11 for Edge Devices

  • 期刊论文

  • 发表日期：

    2025年11月6日

查看全文
  • Hongyu Wang,
  • Zheng Dang,
  • Hanqi Shi,
  • Guangyu Dong,
  • Hongyuan Ye,
  • Rui Wang,
  • Mingzhu Cui

摘要

In response to the demand for lightweight drone target detection in the field of drone countermeasures, a portable drone intelligent detection system based on YOLOv11 is proposed in this study. The system consists of a drone detection module, a data transmission module, and a main station, with the aim of achieving precise drone detection, real-time localization, and data transmission. The core component of the system is the drone detection module, which includes four hardware units: a USB camera, a LubanCat4 development board, a GPS, and a 4G module. It is capable of performing image capture, drone target detection, target height measurement, and real-time positioning. The specific workflow is as follows: images are captured by the USB camera and transmitted to the LubanCat4 development board, where the YOLOv11 algorithm is applied for drone target detection, and information such as the target’s bounding box position and confidence level is output. Based on the target’s bounding box width, camera focal length, pixel size, and other data, the drone’s flight height is measured using the similar triangle method. Real-time positioning data, including latitude and longitude, is provided by the GPS and sent to the development board. Finally, the EC20 4G module is used to upload the drone detection information and GPS positioning data to the main station, enabling remote data transmission. The system offers efficient and accurate drone detection and real-time data transmission capabilities, making it suitable for various drone monitoring applications.