TY - GEN
T1 - Utilizing the sparsity of quasi-distributed sensing systems for sub-Nyquist signal reconstruction
AU - Shiloh, Lihi
AU - Giryes, Raja
AU - Eyal, Avishay
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Compressive Sensing
KW - Fiber Bragg Gratings
KW - Fiber Optic Sensors
KW - Optical Frequency Domain Reflectometry
UR - http://www.scopus.com/inward/record.url?scp=85073319060&partnerID=8YFLogxK
U2 - 10.1117/12.2541252
DO - 10.1117/12.2541252
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AN - SCOPUS:85073319060
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Seventh European Workshop on Optical Fibre Sensors
A2 - Kalli, Kyriacos
A2 - Brambilla, Gilberto
A2 - O'Keeffe, Sinead
PB - SPIE
T2 - 7th European Workshop on Optical Fibre Sensors, EWOFS 2019
Y2 - 1 October 2019 through 4 October 2019
ER -