Field tests of a distributed acoustic sensing system based on temporal adaptive matched filtering of phase-sensitive OTDR signals

Distributed acoustic sensing (DAS) based on phase-sensitive optical time domain reflectometry (OTDR) is being widely used in several applications and attracting significant research interest. The main challenge in coherent detection-based phase-sensitive OTDR systems is the speckle-like background noise which impacts the detection performance and conventional techniques are not suitable for detecting weak vibrations under strong background noise. Recently, we proposed a temporal adaptive filtering (AMF) technique to reduce the background noise in phase-sensitive OTDR systems. The AMF method is based on linear filtering of the optical backscattered signals and the filter coefficients are computed from the observed data. In this study, after briefly reviewing the fundamental theory underlying the adaptive algorithm, we present the effectiveness and performance results of the AMF technique with the field tests. The impact of the diagonal loading level which is used to solve the ill-conditioning of the estimated noise covariance matrix is investigated. Performance dependence of the AMF technique on filter size and a comparison with the conventional trace averaging is presented. It is demonstrated that with the AMF technique, more than 10 dB of SNR values can be achieved without introducing additional optical amplifier stages in the DAS hardware. It is shown that intruder activities 25 m far away from a buried SMF-28 fiber underground can be detected with the proposed technique efficiently.