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arXiv · 2405.01140

Tracking and classifying objects with DAS data along railway

Simon L. B. Fredriksen·The Tien Mai·Kevin Growe·Jo Eidsvik
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Abstract

Distributed acoustic sensing through fiber-optical cables can contribute to traffic monitoring systems. Using data from a day of field testing on a 50 km long fiber-optic cable along a railroad track in Norway, we detect and track cars and trains along a segment of the fiber-optic cable where the road runs parallel to the railroad tracks. We develop a method for automatic detection of events and then use these in a Kalman filter variant known as joint probabilistic data association for object tracking and classification. Model parameters are specified using in-situ log data along with the fiber-optic signals. Running the algorithm over an entire day, we highlight results of counting cars and trains over time and their estimated velocities.

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Simon L. B. Fredriksen, The Tien Mai, Kevin Growe, Jo Eidsvik. 2024-05-02. Tracking and classifying objects with DAS data along railway. https://arxiv.org/abs/2405.01140

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