A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices

Wang, Hongyu; Qu, Yifeng; Dang, Zheng; Wu, Duosheng; Cui, Mingzhu; Shi, Hanqi; Zhao, Jintao

doi:10.3390/s26010205

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Open AccessArticle

A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices

by

Hongyu Wang

^*,

Yifeng Qu

,

Zheng Dang

,

Duosheng Wu

,

Mingzhu Cui

,

Hanqi Shi

and

Jintao Zhao

School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China

^*

Author to whom correspondence should be addressed.

Sensors 2026, 26(1), 205; https://doi.org/10.3390/s26010205 (registering DOI)

Submission received: 27 October 2025 / Revised: 23 December 2025 / Accepted: 25 December 2025 / Published: 28 December 2025

(This article belongs to the Special Issue AI-Based Computer Vision Sensors & Systems—2nd Edition)

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Abstract

The growing threat of unauthorized drones to ground-based critical infrastructure necessitates efficient ground-to-air surveillance systems. This paper proposes a lightweight framework for UAV detection and altitude measurement from a fixed ground perspective. We introduce Ghost-YOLOv11n, an optimized detector that integrates GhostConv modules into YOLOv11n, reducing computational complexity by 12.7% while achieving 98.8% mAP_0.5 on a comprehensive dataset of 8795 images. Deployed on a LuBanCat4 edge device with Rockchip RK3588S NPU acceleration, the model achieves 20 FPS. For stable altitude estimation, we employ an Extended Kalman Filter to refine measurements from a monocular ranging method based on similar-triangle geometry. Experimental results under ground monitoring scenarios show height measurement errors remain within 10% up to 30 m. This work provides a cost-effective, edge-deployable solution specifically for ground-based anti-drone applications.

Keywords: UAV detection; edge AI; YOLOv11; monocular ranging; Kalman filter; embedded deployment

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MDPI and ACS Style

Wang, H.; Qu, Y.; Dang, Z.; Wu, D.; Cui, M.; Shi, H.; Zhao, J. A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices. Sensors 2026, 26, 205. https://doi.org/10.3390/s26010205

AMA Style

Wang H, Qu Y, Dang Z, Wu D, Cui M, Shi H, Zhao J. A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices. Sensors. 2026; 26(1):205. https://doi.org/10.3390/s26010205

Chicago/Turabian Style

Wang, Hongyu, Yifeng Qu, Zheng Dang, Duosheng Wu, Mingzhu Cui, Hanqi Shi, and Jintao Zhao. 2026. "A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices" Sensors 26, no. 1: 205. https://doi.org/10.3390/s26010205

APA Style

Wang, H., Qu, Y., Dang, Z., Wu, D., Cui, M., Shi, H., & Zhao, J. (2026). A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices. Sensors, 26(1), 205. https://doi.org/10.3390/s26010205

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A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices

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