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

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.