Far-field phasing method based on deep learning for tiled-aperture coherent beam combination
Far-field phasing method based on deep learning for tiled-aperture coherent beam combination
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DOI：
10.1016/j.optcom.2022.128928
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发表时间：
2022-08
影响因子：
2.4
通讯作者：
Xunzheng Li;Chun Peng;Xiaoyan Liang
中科院分区：
文献类型：
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作者：
Xunzheng Li;Chun Peng;Xiaoyan Liang
深度学习作为机器学习的一个分支，以其优异的识别能力在光学测量领域受到越来越多的关注。在本研究中，我们应用深度学习方法来测量两光束平铺孔径相干组合系统中远场干涉条纹图案的相位误差。我们进行了数值模拟和实验来验证该方法的有效性。仿真中该定相方法的RMS精度为λ/60，而实验中为λ/30。作为扩展，四光束模拟的测量精度至少达到了λ/40。满足相干合束系统合束效率95%的相位同步要求。
Deep learning, which is a branch of machine learning, has gained increasing attention in the field of optical measurement owing to its excellent recognition ability. In this study, we applied a deep learning method to measure the phase error from the far-field interference fringe pattern in the two-beam tiled-aperture coherent combination system. We performed both numerical simulations and experiments to verify the validity of this method. The RMS accuracy of the phasing method in the simulation was λ/60, whereas in the experiments, it was λ/30. As an extension, the measurement accuracy of the four-beam simulation reached least λ/40. It satisfies the phase synchronization requirements at 95% combining efficiency in the coherent beam combination system.