水下光学成像技术对于海底资源勘测、海洋生态监测、水下搜索救援、水下考古等应用具有重要意义。相比传统水下摄像机，距离选通成像技术可以过滤选通切片外的后向散射噪声和环境背景噪声，实现高质量水下成像，但是在浑浊水体中仍然会受切片内后向散射噪声影响，导致成像距离缩短。对此，开展了光学偏振与距离选通成像结合的水下偏振选通成像技术研究，利用后向散射光良好的保偏性去除选通切片范围内的后向散射噪声，提升目标识别距离。通过理论仿真和实验研究，对比分析了不同水质下距离选通成像和偏振选通成像目标识别距离的差异。发现存在临界衰减系数c₀：当水体衰减系数小于等于c₀时，光学偏振对于提升距离选通成像工作距离无效果；当水体衰减系数大于c₀时，偏振可提升距离选通成像工作距离。实验中还发现，目标反射率会影响临界衰减系数。该研究有利于不同水质下距离选通成像的优化应用。

工业废水分类是水污染防治和水资源管理的前提和基础，相较于生活污水，工业废水的分类研究相对滞后。水体化学需氧量 (COD) 是衡量水体质量的核心指标，针对现有工业废水COD分类算法中预测精度较低的问题，提出基于门控循环单元 (GRU) 的卷积神经网络 (CNN) 混合模型。该模型首先将紫外-可见光谱法测得的工业废水COD数据进行高斯滤波去噪，然后把去噪后的光谱数据输入CNN模型进行特征提取，最后通过GRU神经网络实现工业废水COD分类。实验结果显示，CNN-GRU分类模型经过200次训练后达到收敛, 分类精度达到99.5%，与长短期记忆方法、GRU方法、CNN-LSTM方法相比，该混合模型的分类精度具有显著优势。

Inverse design focuses on identifying photonic structures to optimize the performance of photonic devices. Conventional scalar-based inverse design approaches are insufficient to design photonic devices of anisotropic materials such as lithium niobate (LN). To the best of our knowledge, this work proposes for the first time the inverse design method for anisotropic materials to optimize the structure of anisotropic-material based photonics devices. Specifically, the orientation dependent properties of anisotropic materials are included in the adjoint method, which provides a more precise prediction of light propagation within such materials. The proposed method is used to design ultra-compact wavelength division demultiplexers in the X-cut thin-film lithium niobate (TFLN) platform. By benchmarking the device performances of our method with those of classical scalar-based inverse design, we demonstrate that this method properly addresses the critical issue of material anisotropy in the X-cut TFLN platform. This proposed method fills the gap of inverse design of anisotropic materials based photonic devices, which finds prominent applications in TFLN platforms and other anisotropic-material based photonic integration platforms.

海水折射率测量在海洋学中发挥了重要作用，但对于海洋气候和海水流场监测领域，现有的折射率传感器无法满足应用场景的高精度与高采样率要求。有鉴于此，文中基于光外差干涉原理设计了海水折射率传感器，分析了该原理下的散粒噪声、相位解调噪声对传感器折射率测量的影响，研制了高精度海水折射率传感器样机，其采样频率为24 kHz，折射率变化量测量值的标准偏差为 $1.584\;8\times $$ {10}^{-8}\;\mathrm{R}\mathrm{I}\mathrm{U}$，该技术促进了海水折射率测量在海洋气候及海洋洋流等领域的应用。

Multilayer dielectric gratings (MLDGs) are crucial for pulse compression in picosecond–petawatt laser systems. Bulged nodular defects, embedded in coating stacks during multilayer deposition, influence the lithographic process and performance of the final MLDG products. In this study, the integration of nanosecond laser conditioning (NLC) into different manufacturing stages of MLDGs was proposed for the first time on multilayer dielectric films (MLDFs) and final grating products to improve laser-induced damage performance. The results suggest that the remaining nodular ejection pits introduced by the two protocols exhibit a high nanosecond laser damage resistance, which remains stable when the irradiated laser fluence is more than twice the nanosecond-laser-induced damage threshold (nanosecond-LIDT) of the unconditioned MLDGs. Furthermore, the picosecond-LIDT of the nodular ejection pit conditioned on the MLDFs was approximately 40% higher than that of the nodular defects, and the loss of the grating structure surrounding the nodular defects was avoided. Therefore, NLC is an effective strategy for improving the laser damage resistance of MLDGs.

激光麦克风是一种利用光学多普勒效应获取远场语音信息的技术，其语音质量受到探测系统自身特性、光探测路径以及目标物等多个方面的影响。为了从远距离声场下的目标物获取更高质量的语音信息，文中通过单频声激励实验获得了4种典型目标物（A4纸片、A4纸盒、瓦楞盒、塑料瓶）的声致振动频率响应，发现了其在频率上的非均匀性。在此基础上，提出了一种基于ResUnet和TFGAN网络的激光语音增强方法，其通过ResUnet网络预测去噪梅尔谱图，并利用TFGAN网络由预测的梅尔谱图恢复出激光语音的时域波形。然后，利用实验室自制的激光麦克风在4种目标物上进行了远距离语音采集实验，采用文中提出的方法对采集到的激光麦克风语音进行了处理，并与非线性函数谐波重构法、DNN+谐波重构法进行了比较。最后利用客观语音质量评估（PESQ）和时域分段信噪比（SNRseg）对处理后的激光语音进行了量化评估。实验结果表明，在4种目标物上采集到的激光语音，经过非线性函数谐波重构方法和DNN+谐波重构方法处理后，语音质量均无明显提升，其相应的PESQ和SNRseg分值无明显提高。而经过文中所提的ResUnet+TFGAN网络方法处理后，激光语音取得了更高的PESQ和SNRseg分值，语音质量明显提升。因此，文中提出的方法在激光麦克风应用中具有更好的激光语音增强效果。此外，由实验结果可知，此方法在频率响应一致性较差的目标物上，仍然可以较好地重建频谱，恢复出高质量的语音信息。