State-of-the-Art Methods for Determining the Frequency Shift of Brillouin Scattering in Fiber-Optic Metrology and Sensing (Review)

• Published in: Instruments and experimental techniques (New York) Vol. 65; no. 5; pp. 687 - 710
• Main Authors: Krivosheev, A. I., Barkov, F. L., Konstantinov, Yu. A., Belokrylov, M. E.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.10.2022; Springer Nature B.V
• Subjects: Artificial intelligence; Curve fitting; Electrical Engineering; Fiber optics; Frequency shift; Machine learning; Measurement Science and Instrumentation; Metrology; Optical communication; Physical Chemistry; Physics; Physics and Astronomy; Scattering; Signal detection; Signal to noise ratio; State-of-the-art reviews
• ISSN: 0020-4412; 1608-3180
• DOI: 10.1134/S0020441222050268

This review describes state-of-the-art software and hardware methods for detecting the frequency shift of a stimulated and spontaneous Brillouin scattering spectrum for the needs of the distributed fiber-optic sensors and fiber-optic metrology industry. Current approaches to optical-fiber probing and signal detection are presented. Digital filtering methods that provide an increase in the signal-to-noise ratio of the spectrum are described. A review of Lorentzian curve fitting (LCF) spectrum approximation methods, correlation methods, artificial intelligence methods, and machine learning methods has been made.