2026-10-14T10:40:52Z https://www.scidb.cn/oai

10.57760/sciencedb.06832 2022-12-07T10:46:58Z

2022-12-07 Far-field phasing method based on deep learning for tiled-aperture coherent beam combination doi:10.57760/sciencedb.06832 en In this work, a phase measurement method based on deep learning is proposed, which uses the deep convolutional neural network algorithm to measure the phase error of tiled-aperture coherent beam combination system in the far field. Fig. 1.tiff describes the simulated two-beam far-field interference pattern and the corresponding axial intensity distribution with different phase errors. Fig.2.tiff describes the comparison of simulation results. Fig.3.tiff describes the four-beam far-field interference pattern and the application of amplitude modulation. Fig.4.tiff describes the results of four beam simulation. Fig.5.tiff describes the experimental setup and DCNN training process. Fig.6.tiff describes experimental data and experimental results. phase measurement method ; deep convolutional neural network; tiled-aperture coherent beam combination Xunzheng Li Chun Peng Xiaoyan Liang PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset http://www.doi.org/10.1016/j.optcom.2022.128928 Science Data Bank