The detection of non-Gaussian vibrations with improved spatial resolution and signal-to-noise ratio in distributed sensing

TL;DR

This paper introduces a higher-order cumulants algorithm for phase-sensitive OTDR that effectively detects non-Gaussian vibrations, improving spatial resolution and SNR in fiber-optic distributed sensing applications.

Contribution

It presents a novel higher-order cumulants method for detecting non-Gaussian vibrations in fiber-optic sensing, addressing a gap in existing Gaussian-based approaches.

Findings

Enhanced detection of non-Gaussian vibrations

Improved spatial resolution in sensing

Higher signal-to-noise ratio achieved

Abstract

In fiber-optic distributed sensing, vibration signals are mostly assumed to follow Gaussian distribution for the simplicity of signal processing. However, in real applications, vibration signals often behave as non-Gaussian processes, which have rarely been highly considered. In this paper, a higher-order cumulants algorithm based phase-sensitive optical time-domain reflectometry (OTDR) is proposed to detect and analyze non-Gaussian vibration signals accompanied with noises. When disturbances are applied on the sensing fiber, the distribution probability of Rayleigh backscattering signals will deviate from the ideal Gaussian distribution. The non-Gaussian vibration is then extracted from Gaussian noises based on the probability density distribution. Simulations and experiments are carried out. The experimental results show that the demonstrated method can measure non-Gaussian vibrations with improved signal-to-noise ratio and spatial resolution.