Overview on the state of polarization sensing: application scenarios and anomaly detection algorithms

Given the ubiquity of optical fiber networks in both terrestrial and submarine environments, leveraging these facilities for sensing anomalous conditions alongside telecommunications can provide significant added value. In this context, distributed acoustic sensing (DAS) systems have been widely employed and discussed due to their sensitivity and ability to locate events. However, integrating them within existing networks is complex and expensive. On the other hand, the received state of polarization (SOP) is also sensitive to external factors, and it can be used for sensing: in this case, no extra hardware would be required since the SOP is already estimated in coherent receivers for data demodulation. The sensing information is provided “for free” by the already installed hardware, potentially requiring only a software upgrade. In this work, we analyze the feasibility of using polarization-based sensing to detect anomalous conditions in metropolitan environments. A polarimeter was used to evaluate SOP noise induced by urban factors, while a commercial coherent transceiver was employed to assess SOP estimation noise. We propose two algorithms for processing polarization data: a time-based method called SOP angular speed (SOPAS) and an adaptive, frequency-based approach named SOP-power spectral density gap (SOP-PSDG). These algorithms were compared by processing Stokes vector samples from the polarimeter when different sinusoidal vibrations are applied to the fiber through a mechanical shaker. Results demonstrate that a sampling rate of just a few tens of Hz is sufficient to effectively identify various hazardous conditions, with SOP-PSDG consistently outperforming SOPAS. Additionally, preliminary findings on the performances of these algorithms using SOP samples from a commercial coherent receiver are discussed.