Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing

Multiple mechanized ocean vessels, including both surface ships and submerged vehicles, can be simultaneously monitored over instantaneous continental-shelf scale regions >10,000 km 2 via passive ocean acoustic waveguide remote sensing. A large-aperture densely-sampled coherent hydrophone array s...

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Published in:Remote Sensing
Main Authors: Chenyang Zhu, Heriberto Garcia, Anna Kaplan, Matthew Schinault, Nils Olav Handegard, Olav Rune Godø, Wei Huang, Purnima Ratilal
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2018
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Online Access:https://doi.org/10.3390/rs10111699
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spelling ftmdpi:oai:mdpi.com:/2072-4292/10/11/1699/ 2023-08-20T04:08:50+02:00 Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing Chenyang Zhu Heriberto Garcia Anna Kaplan Matthew Schinault Nils Olav Handegard Olav Rune Godø Wei Huang Purnima Ratilal agris 2018-10-29 application/pdf https://doi.org/10.3390/rs10111699 EN eng Multidisciplinary Digital Publishing Institute Ocean Remote Sensing https://dx.doi.org/10.3390/rs10111699 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 11; Pages: 1699 passive ocean acoustic waveguide remote sensing multiple ships ship noise tonal ship detection localization classification beamforming triangulation hydrophone array passive acoustics Text 2018 ftmdpi https://doi.org/10.3390/rs10111699 2023-07-31T21:48:29Z Multiple mechanized ocean vessels, including both surface ships and submerged vehicles, can be simultaneously monitored over instantaneous continental-shelf scale regions >10,000 km 2 via passive ocean acoustic waveguide remote sensing. A large-aperture densely-sampled coherent hydrophone array system is employed in the Norwegian Sea in Spring 2014 to provide directional sensing in 360 degree horizontal azimuth and to significantly enhance the signal-to-noise ratio (SNR) of ship-radiated underwater sound, which improves ship detection ranges by roughly two orders of magnitude over that of a single hydrophone. Here, 30 mechanized ocean vessels spanning ranges from nearby to over 150 km from the coherent hydrophone array, are detected, localized and classified. The vessels are comprised of 20 identified commercial ships and 10 unidentified vehicles present in 8 h/day of Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) observation for two days. The underwater sounds from each of these ocean vessels received by the coherent hydrophone array are dominated by narrowband signals that are either constant frequency tonals or have frequencies that waver or oscillate slightly in time. The estimated bearing-time trajectory of a sequence of detections obtained from coherent beamforming are employed to determine the horizontal location of each vessel using the Moving Array Triangulation (MAT) technique. For commercial ships present in the region, the estimated horizontal positions obtained from passive acoustic sensing are verified by Global Positioning System (GPS) measurements of the ship locations found in a historical Automatic Identification System (AIS) database. We provide time-frequency characterizations of the underwater sounds radiated from the commercial ships and the unidentified vessels. The time-frequency features along with the bearing-time trajectory of the detected signals are applied to simultaneously track and distinguish these vessels. Text Norwegian Sea MDPI Open Access Publishing Norwegian Sea Remote Sensing 10 11 1699
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic passive ocean acoustic waveguide remote sensing
multiple ships
ship noise
tonal
ship detection
localization
classification
beamforming
triangulation
hydrophone array
passive acoustics
spellingShingle passive ocean acoustic waveguide remote sensing
multiple ships
ship noise
tonal
ship detection
localization
classification
beamforming
triangulation
hydrophone array
passive acoustics
Chenyang Zhu
Heriberto Garcia
Anna Kaplan
Matthew Schinault
Nils Olav Handegard
Olav Rune Godø
Wei Huang
Purnima Ratilal
Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing
topic_facet passive ocean acoustic waveguide remote sensing
multiple ships
ship noise
tonal
ship detection
localization
classification
beamforming
triangulation
hydrophone array
passive acoustics
description Multiple mechanized ocean vessels, including both surface ships and submerged vehicles, can be simultaneously monitored over instantaneous continental-shelf scale regions >10,000 km 2 via passive ocean acoustic waveguide remote sensing. A large-aperture densely-sampled coherent hydrophone array system is employed in the Norwegian Sea in Spring 2014 to provide directional sensing in 360 degree horizontal azimuth and to significantly enhance the signal-to-noise ratio (SNR) of ship-radiated underwater sound, which improves ship detection ranges by roughly two orders of magnitude over that of a single hydrophone. Here, 30 mechanized ocean vessels spanning ranges from nearby to over 150 km from the coherent hydrophone array, are detected, localized and classified. The vessels are comprised of 20 identified commercial ships and 10 unidentified vehicles present in 8 h/day of Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) observation for two days. The underwater sounds from each of these ocean vessels received by the coherent hydrophone array are dominated by narrowband signals that are either constant frequency tonals or have frequencies that waver or oscillate slightly in time. The estimated bearing-time trajectory of a sequence of detections obtained from coherent beamforming are employed to determine the horizontal location of each vessel using the Moving Array Triangulation (MAT) technique. For commercial ships present in the region, the estimated horizontal positions obtained from passive acoustic sensing are verified by Global Positioning System (GPS) measurements of the ship locations found in a historical Automatic Identification System (AIS) database. We provide time-frequency characterizations of the underwater sounds radiated from the commercial ships and the unidentified vessels. The time-frequency features along with the bearing-time trajectory of the detected signals are applied to simultaneously track and distinguish these vessels.
format Text
author Chenyang Zhu
Heriberto Garcia
Anna Kaplan
Matthew Schinault
Nils Olav Handegard
Olav Rune Godø
Wei Huang
Purnima Ratilal
author_facet Chenyang Zhu
Heriberto Garcia
Anna Kaplan
Matthew Schinault
Nils Olav Handegard
Olav Rune Godø
Wei Huang
Purnima Ratilal
author_sort Chenyang Zhu
title Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing
title_short Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing
title_full Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing
title_fullStr Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing
title_full_unstemmed Detection, Localization and Classification of Multiple Mechanized Ocean Vessels over Continental-Shelf Scale Regions with Passive Ocean Acoustic Waveguide Remote Sensing
title_sort detection, localization and classification of multiple mechanized ocean vessels over continental-shelf scale regions with passive ocean acoustic waveguide remote sensing
publisher Multidisciplinary Digital Publishing Institute
publishDate 2018
url https://doi.org/10.3390/rs10111699
op_coverage agris
geographic Norwegian Sea
geographic_facet Norwegian Sea
genre Norwegian Sea
genre_facet Norwegian Sea
op_source Remote Sensing; Volume 10; Issue 11; Pages: 1699
op_relation Ocean Remote Sensing
https://dx.doi.org/10.3390/rs10111699
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs10111699
container_title Remote Sensing
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