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arXiv · 1904.06659

Computational distributed fiber-optic sensing

Da-Peng Zhou·Wei Peng·Liang Chen·Xiaoyi Bao
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Abstract

Ghost imaging allows image reconstruction by correlation measurements between a light beam that interacts with the object without spatial resolution 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.

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Da-Peng Zhou, Wei Peng, Liang Chen, Xiaoyi Bao. 2019-04-14. Computational distributed fiber-optic sensing. https://doi.org/10.1364/oe.27.017069

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