基于物体检测的照明环境中 LED 背光的高精度自动光轴对准

IF 0.3 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Yuma Nishimura;Wataru Chujo;Kentaro Kobayashi
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引用次数: 0

摘要

高吞吐量光无线通信(OWC)的研究正在向第六代迈进。由于由发光二极管和光电二极管组成的近红外 600 Mbps 发光二极管回程(LEDBH)的半功率光束宽度较窄,因此 LEDBH 的高精度光轴对准非常重要。迄今为止,光轴都是通过瞄准镜手动对准的。在本研究中,利用深度学习的对象检测(YOLOv7)来自动对准光轴。在改变相机曝光时间的同时,对照明环境中 LEDBH 检测的平均精度进行了评估。通过物体检测和机械角度调整对光轴进行了微调。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-Precision Automatic Optical Axis Alignment of LED Backhaul in Lighting Surroundings Based on Object Detection
Research on high-throughput optical wireless communication (OWC) has been progressing toward sixth generation. As half-power beam width of near-infrared 600 Mbps light emitting diode backhaul (LEDBH) consisting of LED and photodiode is narrow, high-precision optical axis alignment of LEDBH is important. So far, the optical axis was manually aligned using a scope. In this study, object detection using deep learning, YOLOv7, is adapted to automatically align the optical axis. Average precisions of LEDBH detection are evaluated in lighting surroundings while changing the camera exposure time. The optical axis is finely adjusted with object detection and mechanical angle adjustment.
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来源期刊
IEICE Communications Express
IEICE Communications Express ENGINEERING, ELECTRICAL & ELECTRONIC-
自引率
33.30%
发文量
114
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