微纳尺度光纤布拉格光栅折射率传感的理论研究

亚波长直径微纳光纤强倏逝场传输的光学特性,使其对周围介质折射率的变化具有极高的灵敏度.本文提出一种基于微纳尺度光纤布拉格光栅(MNFBG)的折射率传感器,结合微纳光纤倏逝场传输和光纤布拉格光栅(FBG)强波长选择的特性来实现高精度折射率传感,对其制备可行性进行了讨论.论文中对MNFBG折射率传感机理进行了深入的理论分析,并使用OptiGrating软件进行了数值模拟,模拟数据显示MNFBG折射率测量的灵敏度随着光纤半径的减小而增加,其中光纤半径为400 nm的MNFBG灵敏度可达到993 nm/RIU,相比于包层蚀刻的FBG灵敏度增加了170倍,说明MNFBG对发展微型化、高灵敏度折射率传感器具有良好的应用前景. 关键词： 微纳光纤 光纤布拉格光栅 折射率传感     

压缩感知在宽带声学多普勒测速技术中的应用

为降低宽带声学多普勒测速技术中宽带回波信号处理系统的采样和数据存储压力,研究了压缩感知的回波信号重构算法,并将其应用于宽带声学多普勒测速的回波信号分析中.在点回波模型下进行宽带回波信号的仿真实验,利用复协方差法计算频移.仿真实验结果表明,在无噪声的理想条件下,利用压缩感知理论处理宽带多普勒测速的回波信号,能够达到理想的...     

Computer Simulation of a 3-D Sensing System with Structured Illumination

A computer simulation system of three-dimensional sensing with structured illumination is presented. It includes the generation of deformed fringe patterns from 3-D shapes and the reconstruction of 3-D shapes, conversely. Some experimental results of the deformed fringe pattern and the reconstructed object shapes are presented. We have also discussed the effect of some major system parameters on the measurement results and considered how to correct these parameters according to the measurement result of the standard plane. Using this simulation system, the major system parameters: environmental conditions, measurement accuracy and algorithm evaluation of the 3-D shape measurement system based on PMP, FTP, SPM, etc., can be researched. © 1997 Elsevier Science Ltd. All rights reserved.     

基于相位一致性的实时压缩跟踪方法

针对基于压缩感知的目标跟踪算法在跟踪过程中,光照剧烈变化引起跟踪不稳定或跟踪失败的问题,本文提出了一种基于相位一致性的改进跟踪方法.该方法利用相位一致性图像特征对光照变化不敏感的特点,首先对样本搜索区域内的图像进行相位一致性变换,然后再提取变换后相位一致性图像的特征,将其用于分类器中来确定目标位置.实验结果表明,该方法在目标受到光照剧烈变化影响的情况下具有很强的适应性,在目标大小为50pixel×55pixel时平均处理帧频可达22fps.与已有基于压缩感知跟踪算法相比,该算法在光照变化剧烈的情况下仍具有很好的鲁棒性,而且在目标尺度和纹理发生一定变化的情况下跟踪稳定.     

大口径合成孔径激光成像雷达演示样机及其实验室验证

合成孔径激光成像雷达(SAIL)的主要技术指标如光学足趾尺寸和成像分辨率等都必须在所设计的远距离传输后实现.提出了一种在实验室空间近距离实现SAIL全系统贯通验证的方法,即在SAIL中附加光学装置使得其在近距离产生发射光束的准几何投影和足够大的外差接收视场,从而产生近距离二维SAIL成像必需的并且适当的光学足趾和方位向...     

平面圆形膜片式光纤布拉格光栅温度补偿压强传感

报道了利用光纤布拉格光栅反射波谱带宽展宽技术实现温度补偿的压强传感新方案。结合平面圆形膜片应变调谐的特点,采用膜盒式结构,将光纤光栅中心对准平面圆形膜片零应变半径并沿径向粘贴,利用反射波谱带宽对应变敏感而对温度不敏感的特性解调压强,成功地实现了温度补偿的压强传感测量。基于光谱分析仪0.05nm的光谱分辨力,实验测得带宽随压强响应灵敏度为0.34nm/MPa,压强精度为±0.15MPa,压强测量范围为0~7.5MPa。实验结果与理论分析基本一致。     

三维面形测量技术的新进展

三维面形测量是获取物质形态特征的一种重要手段，也是记录，比较，复制物体形态特征 的基础，三维面形测量技术在机器视觉，自动加工，工业检测，产品质量控制，实物仿形，生物和医学等领域具有重要意义和广阔的应用前景。     

多角度偏振辐射计系统设计与实现

多角度和偏振遥感可解决传统遥感所不能解决的大气探测和目标识别等方面的问题。为实现气溶胶偏振信息的多角度探测,提出了一种新型的多角度偏振辐射计。该辐射计可以在多个角度上测量大气的偏振光谱信息,为大气光学和微物理特性的高精度反演提供重要的实测数据源。作为航天载荷的原理样机,多角度偏振辐射计的光机系统由多路并行望远光学模块组成,可在110°视场范围内,以0.5°间隔实现偏振信息的多角度探测;采集控制与数据传输系统由双控制核心和高速接口组成,大大提高了系统的并行处理能力和数据传输速度,可在高速运动的平台上实现多路偏振光谱信息的同步采集与实时传输,避免了由平台移动和信号的异步采集引入的误差。航飞试验结果表明,多角度偏振辐射计可实现气溶胶偏振信息的高精度探测。     

Adsorption-controlled transition of the electrical properties realized in Hematite（alpha-Fe2O3） nanorods ethanol sensing

Alpha-Fe2O3 nanorods are synthesized through a hydrothermal method with no surfactant introduced and ethanol sensors are fabricated from these nanorods.The device can respond to ethanol vapour in a concentration range from 1 to 1500 parts per million and shows both p-type and n-type responding characteristics during the investigation of the ethanol sensing.The sensor displays a p-type characteristic when the ethanol concentration is low and converted into an n-type characteristic as the concentration exceeds a certain value.Such a phenomenon is attributed to the chemisorbed oxygen,which leads to different modifications of the energy band at the surface,namely,depletion layer or inversion layer.     

Learnable three-dimensional Gabor convolutional network with global affinity attention for hyperspectral image classification

Benefiting from the development of hyperspectral imaging technology, hyperspectral image (HSI) classification has become a valuable direction in remote sensing image processing. Recently, researchers have found a connection between convolutional neural networks (CNNs) and Gabor filters. Therefore, some Gabor-based CNN methods have been proposed for HSI classification. However, most Gabor-based CNN methods still manually generate Gabor filters whose parameters are empirically set and remain unchanged during the CNN learning process. Moreover, these methods require patch cubes as network inputs. Such patch cubes may contain interference pixels, which will negatively affect the classification results. To address these problems, in this paper, we propose a learnable three-dimensional (3D) Gabor convolutional network with global affinity attention for HSI classification. More precisely, the learnable 3D Gabor convolution kernel is constructed by the 3D Gabor filter, which can be learned and updated during the training process. Furthermore, spatial and spectral global affinity attention modules are introduced to capture more discriminative features between spatial locations and spectral bands in the patch cube, thus alleviating the interfering pixels problem. Experimental results on three well-known HSI datasets (including two natural crop scenarios and one urban scenario) have demonstrated that the proposed network can achieve powerful classification performance and outperforms widely used machine-learning-based and deep-learning-based methods.