Tracking and classifying objects with DAS data along railway
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866913339442987008 |
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| author | Fredriksen, Simon L. B. Mai, The Tien Growe, Kevin Eidsvik, Jo |
| author_facet | Fredriksen, Simon L. B. Mai, The Tien Growe, Kevin Eidsvik, Jo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_01140 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Tracking and classifying objects with DAS data along railway Fredriksen, Simon L. B. Mai, The Tien Growe, Kevin Eidsvik, Jo Applications 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. |
| title | Tracking and classifying objects with DAS data along railway |
| topic | Applications |
| url | https://arxiv.org/abs/2405.01140 |