Multi-Sensor Satellite Data Processing for Marine Traffic Understanding

The work described in this document concerns the estimation of the kinematics of a navigating vessel. This task can be accomplished through the exploitation of satellite-borne systems for Earth observation. Indeed, Synthetic Aperture Radar (SAR) and optical sensors installed aboard satellites (Europ...

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Main Authors: Marco Reggiannini, Luigi Bedini
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Electronics
Subjects:
SAR
Online Access:https://www.mdpi.com/2079-9292/8/2/152
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spelling doaj-97b7e0ca97844fe28054343276aec9df2020-11-25T01:59:04ZengMDPI AGElectronics2079-92922019-02-018215210.3390/electronics8020152electronics8020152Multi-Sensor Satellite Data Processing for Marine Traffic UnderstandingMarco Reggiannini0Luigi Bedini1Institute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, ItalyThe work described in this document concerns the estimation of the kinematics of a navigating vessel. This task can be accomplished through the exploitation of satellite-borne systems for Earth observation. Indeed, Synthetic Aperture Radar (SAR) and optical sensors installed aboard satellites (European Space Agency Sentinel, ImageSat International Earth Remote Observation System, Italian Space Agency Constellation of Small Satellites for Mediterranean basin Observation) return multi-resolution maps providing information about the marine surface. A moving ship represented through satellite imaging results in a bright oblong object, with a peculiar wake pattern generated by the ship’s passage throughout the water. By employing specifically tailored computer vision methods, these vessel features can be identified and individually analyzed for what concerns geometrical and radiometric properties, backscatterers spatial distribution and the spectral content of the wake components. This paper proposes a method for the automatic detection of the vessel’s motion-related features and their exploitation to provide an estimation of the vessel velocity vector. In particular, the ship’s related wake pattern is considered as a crucial target of interest for the purposes mentioned. The corresponding wake detection module has been implemented adopting a novel approach, i.e., by introducing a specifically tailored gradient estimator in the early processing stages. This results in the enhancement of the turbulent wake detection performance. The resulting overall procedure may also be included in marine surveillance systems in charge of detecting illegal maritime traffic, combating unauthorized fishing, irregular migration and related smuggling activities.https://www.mdpi.com/2079-9292/8/2/152remote sensingSARradon transformspeckle noise filteringmaritime traffic monitoringwake detection and analysis
collection DOAJ
language English
format Article
sources DOAJ
author Marco Reggiannini
Luigi Bedini
spellingShingle Marco Reggiannini
Luigi Bedini
Multi-Sensor Satellite Data Processing for Marine Traffic Understanding
Electronics
remote sensing
SAR
radon transform
speckle noise filtering
maritime traffic monitoring
wake detection and analysis
author_facet Marco Reggiannini
Luigi Bedini
author_sort Marco Reggiannini
title Multi-Sensor Satellite Data Processing for Marine Traffic Understanding
title_short Multi-Sensor Satellite Data Processing for Marine Traffic Understanding
title_full Multi-Sensor Satellite Data Processing for Marine Traffic Understanding
title_fullStr Multi-Sensor Satellite Data Processing for Marine Traffic Understanding
title_full_unstemmed Multi-Sensor Satellite Data Processing for Marine Traffic Understanding
title_sort multi-sensor satellite data processing for marine traffic understanding
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2019-02-01
description The work described in this document concerns the estimation of the kinematics of a navigating vessel. This task can be accomplished through the exploitation of satellite-borne systems for Earth observation. Indeed, Synthetic Aperture Radar (SAR) and optical sensors installed aboard satellites (European Space Agency Sentinel, ImageSat International Earth Remote Observation System, Italian Space Agency Constellation of Small Satellites for Mediterranean basin Observation) return multi-resolution maps providing information about the marine surface. A moving ship represented through satellite imaging results in a bright oblong object, with a peculiar wake pattern generated by the ship’s passage throughout the water. By employing specifically tailored computer vision methods, these vessel features can be identified and individually analyzed for what concerns geometrical and radiometric properties, backscatterers spatial distribution and the spectral content of the wake components. This paper proposes a method for the automatic detection of the vessel’s motion-related features and their exploitation to provide an estimation of the vessel velocity vector. In particular, the ship’s related wake pattern is considered as a crucial target of interest for the purposes mentioned. The corresponding wake detection module has been implemented adopting a novel approach, i.e., by introducing a specifically tailored gradient estimator in the early processing stages. This results in the enhancement of the turbulent wake detection performance. The resulting overall procedure may also be included in marine surveillance systems in charge of detecting illegal maritime traffic, combating unauthorized fishing, irregular migration and related smuggling activities.
topic remote sensing
SAR
radon transform
speckle noise filtering
maritime traffic monitoring
wake detection and analysis
url https://www.mdpi.com/2079-9292/8/2/152
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AT luigibedini multisensorsatellitedataprocessingformarinetrafficunderstanding
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