2026-10-11T06:49:26Z https://www.scidb.cn/oai

10.57760/sciencedb.06837 2022-12-07T10:47:01Z

2022-12-07 Deep learning assisted far-field multi-beam pointing measurement doi:10.57760/sciencedb.06837 en In this work, we present a deep learning approach to synchronously measure the multi-beam pointing error. This approach uses only one detector to identify the pointing change of the far-field spot by the deep convolutional neural network algorithm. It can be well applied to multi-beam coherent combination for high-power laser systems.Figure1.tif describes the simulated two-beam far-field interference pattern. Figure2.tif describes the training and measurement process of DCNN. Figure3.tif describes the experimental sample acquisition setup. Figure4.tif describes the experimental far-field interference pattern and the experimental results. multi-beam pointing; Deep learning; coherent beam combination Xunzheng Li Chun Peng Xiaoyan Liang PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset http://www.doi.org/10.1117/1.oe.62.8.086102 Science Data Bank