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

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.

Automated summary

This review provides an overview of state-of-the-art software and hardware methods for detecting the frequency shift of a stimulated and spontaneous Brillouin scattering spectrum in the distributed fiber-optic sensors and fiber-optic metrology industry. It discusses current approaches to optical-fiber probing and signal detection, as well as digital filtering methods to improve the signal-to-noise ratio of the spectrum. The review also covers Lorentzian curve fitting (LCF) spectrum approximation methods, correlation methods, artificial intelligence methods, and machine learning methods.