@inproceedings{7564d4a6b1da4458b32a61ca08a84be2,
title = "Utilizing the sparsity of quasi-distributed sensing systems for sub-Nyquist signal reconstruction",
abstract = "Quasi-distributed sensing, e.g. Quasi-Distributed Acoustic Sensing (Q-DAS), with optical fibers is commonly used for various applications. Its excellent performance is well known, however, it necessitates high sampling rates and expensive hardware for acquisition and processing. In this paper, we introduce a technique, based on Compressed Sensing (CS) theory, to locate discrete reflectors' along a sensing fiber with a smaller number of samples than required according to Nyquist criterion. The technique is based on the fact that the fiber profile consists of a limited number of discrete reflectors and significantly weaker reflections of Rayleigh back-scatterers, and thus can be approximated as a sparse signal. The task of reconstructing a sparse signal from a sub-Nyquist sampled signal using Orthogonal Matching Pursuit (OMP) is presented and tested experimentally.",
keywords = "Compressive Sensing, Fiber Bragg Gratings, Fiber Optic Sensors, Optical Frequency Domain Reflectometry",
author = "Lihi Shiloh and Raja Giryes and Avishay Eyal",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; 7th European Workshop on Optical Fibre Sensors, EWOFS 2019 ; Conference date: 01-10-2019 Through 04-10-2019",
year = "2019",
doi = "https://doi.org/10.1117/12.2541252",
language = "الإنجليزيّة",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Kyriacos Kalli and Gilberto Brambilla and Sinead O'Keeffe",
booktitle = "Seventh European Workshop on Optical Fibre Sensors",
address = "الولايات المتّحدة",
}