1 中国科学院自适应光学重点实验室，四川 成都 610209
2 中国科学院光电技术研究所，四川 成都 610209
3 中国科学院大学电子电气与通信工程学院，北京 100049
自适应光学（AO）技术是一种能够补偿大气湍流的有效手段，但由于存在系统固有时延，变形镜（DM）上的补偿波前滞后于实测畸变波前，导致AO技术对高时间频率大气湍流的校正效果明显下降。因此，开展大气湍流前向预测研究对于抵消AO系统固有时延、提升系统校正带宽具有重要的研究意义和应用价值。本文提出了一种基于注意力机制的AO波前时空预测网络，该网络同时考虑了大气湍流的时间与空间特征，可通过连续6帧先验波前斜率信息预测未来第2帧的波前斜率。在具有两帧延迟的AO系统仿真中，所提预测网络使得波前校正残差均方根（RMS）下降了约40%，并且在不同的大气湍流强度下均表现出稳定的预测精度，预测残差RMS仅为真实畸变波前RMS的5.00%。最后使用1 km激光大气传输系统采集的实验数据进行了测试，验证了开环斜率预测网络的有效性。
自适应光学 时延误差 注意力机制 波前预测
Author Affiliations
Abstract
1 Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu 610209, China
2 Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
3 School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
A real-time wavefront sensing method for arbitrary targets is proposed, which provides an effective way for diversified wavefront sensing application scenarios. By using a distorted grating, the positive and negative defocus images are simultaneously acquired on a single detector. A fine feature, which is independent of the target itself but corresponding to the wavefront aberration, is defined. A lightweight and efficient network combined with an attention mechanism (AM-EffNet) is proposed to establish an accurate mapping between the features and the incident wavefronts. Comparison results show that the proposed method has superior performance compared to other methods and can achieve high-accuracy wavefront sensing in varied target scenes only by using the point target dataset to train the network well.
wavefront sensing distorted grating fine feature Chinese Optics Letters
2023, 21(6): 060101
