Adaptive Power Thresholding for Real Time Threat Detection in Distributed Acoustic Sensing Systems

In this paper, an adaptive power thresholding approach for real time treat detection on fiber optic based distributed acoustic sensing systems is presented. Since, the measured signal magnitude changes due to the optical system internal mechanisms and physical activities applied near the fiber optic cable and there is no approved statistical signal model, signal statistics are generated from the captured data directly. Since, it is not known a priori that the captured data contains only noise or noisy activity data, power threshold is computed by applying two step statistical model approach. To do this, first and second order Gaussian mixture models are tested and the most appropriate is used for computing power threshold. Additionally, the update mechanism of power thresholding is explained and the execution time of the algorithm is analyzed.