High-Precision Acoustic Event Monitoring in Single-Mode Fibers Using Fisher Information

TL;DR

This paper introduces an optimization method using Fisher information to enhance the sensitivity and precision of polarization optical fiber sensors for acoustic detection, resulting in significantly improved signal-to-noise ratios and broadband signal reconstruction.

Contribution

It presents a novel Fisher information-based polarization state optimization technique for fiber sensors, improving their sensitivity and broadband acoustic detection capabilities.

Findings

Signal-to-noise ratio increased from 4.3 to 37.6 dB

Achieved flat sensor response from 1.5 kHz to 15 kHz

Demonstrated high-precision broadband acoustic signal reconstruction

Abstract

Polarization optical fiber sensors are based on modifications of fiber birefringence by an external measurand (e.g. strain, pressure, acoustic waves). Yet, this means that different input states of polarization will result in very distinct behaviors, which may or may not be optimal in terms of sensitivity and signal-to-noise ratio. To tackle this challenge, this manuscript presents an optimization technique for the input polarization state using the Fisher information formalism, which allows for achieving maximal precision for a statistically unbiased metric. By first measuring the variation of the Mueller matrix of the optical fiber in response to controlled acoustic perturbations induced by piezo speakers, we compute the corresponding Fisher information operator. Using maximal information states of the Fisher information, it was possible to observe a significant improvement in the performance of the sensor, increasing the signal-to-noise ratio from 4.3 to 37.6 dB, attaining an almost flat response from 1.5 kHz up to 15 kHz. As a proof-of-concept for dynamic audio signal detection, a broadband acoustic signal was also reconstructed with significant gain, demonstrating the usefulness of the introduced formalism for high-precision sensing with polarimetric fiber sensors.