个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:滑铁卢大学
学位:博士
所在单位:物理学院
电子邮箱:dpzhou@dlut.edu.cn
Computational distributed fiber-optic sensing
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论文类型:期刊论文
发表时间:2019-06-10
发表刊物:OPTICS EXPRESS
收录刊物:SCIE、EI
卷号:27
期号:12
页面范围:17069-17079
ISSN号:1094-4087
关键字:Binary sequences; Cost reduction; Fiber optics; Image reconstruction; Imaging techniques; Object detection, Backscattered light; Correlation measurement; Distributed fiber optic sensor; Fiber-optic sensing; Orders of magnitude; Scattering information; Spatially resolved; Temporal images, Fiber optic sensors
摘要:Ghost imaging allows image reconstruction by correlation measurements between a light beam that interacts with the object without spatially resolved detection and a spatially resolved light beam that never interacts with the object. The two light beams are copies of each other. Its computational version removes the requirement of a spatially resolved detector when the light intensity pattern is pre-known. Here, we exploit the temporal analogue of computational ghost imaging, and demonstrate a computational distributed fiber-optic sensing technique. Temporal images containing spatially distributed scattering information used for sensing purposes are retrieved through correlating the "integrated" backscattered light and the pre-known binary patterns. The sampling rate required for our technique is inversely proportional to the total time duration of a binary sequence, so that it can be significantly reduced compared to that of the traditional methods. Our experiments demonstrate a 3 orders of magnitude reduction in the sampling rate, offering great simplification and cost reduction in the distributed fiber-optic sensors. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement