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Passive radar imaging of ship targets with GNSS signals of opportunity / Debora Pastina in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 2627 - 2742 Titre : Passive radar imaging of ship targets with GNSS signals of opportunity Type de document : Article/Communication Auteurs : Debora Pastina, Auteur ; Fabrizio Santi, Auteur ; Federica Pieralice, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2627 - 2742 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] capteur passif [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] cible mobile [Termes descripteurs IGN] détection de cible [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] image radar [Termes descripteurs IGN] navigation maritime [Termes descripteurs IGN] navire [Termes descripteurs IGN] radar bistatique [Termes descripteurs IGN] signal GNSS [Termes descripteurs IGN] télédétection spatiale Résumé : (Auteur) This article explores the possibility to exploit global navigation satellite systems (GNSS) signals to obtain radar imagery of ships. This is a new application area for the GNSS remote sensing, which adds to a rich line of research about the alternative utilization of navigation satellites for remote sensing purposes, which currently includes reflectometry, passive radar, and synthetic aperture radar (SAR) systems. In the field of short-range maritime surveillance, GNSS-based passive radar has already proven to detect and localize ship targets of interest. The possibility to obtain meaningful radar images of observed vessels would represent an additional benefit, opening the doors to noncooperative ship classification capability with this technology. To this purpose, a proper processing chain is here conceived and developed, able to achieve well-focused images of ships while maximizing their signal-to-background ratio. Moreover, the scaling factors needed to map the backscatter energy in the range and cross-range domain are also analytically derived, enabling the estimation of the length of the target. The effectiveness of the proposed approach at obtaining radar images of ship targets and extracting relevant features is confirmed via an experimental campaign, comprising multiple Galileo satellites and a commercial ferry undergoing different kinds of motion. Numéro de notice : A2021-218 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3005306 date de publication en ligne : 16/07/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3005306 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97210 [article]

Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC4A / Pierre Bosser in Earth System Science Data, vol 13 n° inconnu ([01/01/2021])  

Public [article]  inEarth System Science Data > vol 13 n° inconnu [01/01/2021] Titre : Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC4A Type de document : Article/Communication Auteurs : Pierre Bosser , Auteur ; Olivier Bock , Auteur ; Cyrille Flamant, Auteur ; Sandrine Bony, Auteur ; Sabrina Speich, Auteur Année de publication : 2021 Projets : 3-projet - voir note / Note générale : bibliographie projets GEMMOC and VEGAN du CNRS program LEFE/INSU Both the raw GNSS measurements and the IWV estimates are available through the AERIS data center (https://en.aeris-data.fr/). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] coordonnées GNSS [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] navire [Termes descripteurs IGN] station permanente [Termes descripteurs IGN] teneur intégrée en vapeur d'eau Résumé : (auteur) In the framework of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open Tropical Atlantic Ocean using Global Navigation Satellite Systems (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian, and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Center for Medium-range Weather Forecast (ECMWF) fifth ReAnalysis (ERA5), from the Moderate-Resolution Imaging Spectroradiometer (MODIS) infra-red products, and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWVs retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (RMS) difference about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with RMS difference of 6 kg m−2 which are very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared product show large RMS differences of 5–7 kg m−2, reflecting the enhanced uncertainties of this satellite product in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Numéro de notice : A2021-064 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/essd-2020-282 En ligne : https://doi.org/10.5194/essd-2020-282 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96840 [article]

Deep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg–ship discrimination / Frederik Hass in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 12 (December 2020) . - n° 758 Titre : Deep learning for detecting and classifying ocean objects: application of YoloV3 for iceberg–ship discrimination Type de document : Article/Communication Auteurs : Frederik Hass, Auteur ; Jamal Jokar Arsanjani, Auteur Année de publication : 2020 Article en page(s) : n° 758 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] Groenland [Termes descripteurs IGN] hydrocarbure [Termes descripteurs IGN] iceberg [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] navire [Termes descripteurs IGN] océan [Termes descripteurs IGN] seuillage d'image [Termes descripteurs IGN] trafic maritime Résumé : (auteur) Synthetic aperture radar (SAR) plays a remarkable role in ocean surveillance, with capabilities of detecting oil spills, icebergs, and marine traffic both at daytime and at night, regardless of clouds and extreme weather conditions. The detection of ocean objects using SAR relies on well-established methods, mostly adaptive thresholding algorithms. In most waters, the dominant ocean objects are ships, whereas in arctic waters the vast majority of objects are icebergs drifting in the ocean and can be mistaken for ships in terms of navigation and ocean surveillance. Since these objects can look very much alike in SAR images, the determination of what objects actually are still relies on manual detection and human interpretation. With the increasing interest in the arctic regions for marine transportation, it is crucial to develop novel approaches for automatic monitoring of the traffic in these waters with satellite data. Hence, this study aims at proposing a deep learning model based on YoloV3 for discriminating icebergs and ships, which could be used for mapping ocean objects ahead of a journey. Using dual-polarization Sentinel-1 data, we pilot-tested our approach on a case study in Greenland. Our findings reveal that our approach is capable of training a deep learning model with reliable detection accuracy. Our methodical approach along with the choice of data and classifiers can be of great importance to climate change researchers, shipping industries and biodiversity analysts. The main difficulties were faced in the creation of training data in the Arctic waters and we concluded that future work must focus on issues regarding training data. Numéro de notice : A2020-808 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9120758 date de publication en ligne : 19/12/2020 En ligne : https://doi.org/10.3390/ijgi9120758 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96953 [article]

Ship detection in SAR images via local contrast of Fisher vectors / Xueqian Wang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 9 (September 2020) . - pp 6467 - 6479 Titre : Ship detection in SAR images via local contrast of Fisher vectors Type de document : Article/Communication Auteurs : Xueqian Wang, Auteur ; Gang Li, Auteur ; Xiao-Ping Zhang, Auteur ; You He, Auteur Année de publication : 2020 Article en page(s) : pp 6467 - 6479 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] algorithme de superpixels [Termes descripteurs IGN] contraste local [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] détection de cible [Termes descripteurs IGN] distribution de Fisher [Termes descripteurs IGN] fouillis d'échos [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] navire [Termes descripteurs IGN] processus gaussien [Termes descripteurs IGN] rapport signal sur bruit Résumé : (auteur) Existing superpixel-based detection algorithms for ship targets in synthetic aperture radar (SAR) images are often derived from the local contrast of intensities (i.e., the local contrast of the first-order information of superpixels) leading to deteriorating performance in low signal-to-clutter ratio (SCR) cases due to the low contrast between the intensities of targets and the clutter. In this article, we propose a new superpixel-based detector to improve the performance of ship target detection in SAR images via the local contrast of fisher vectors (LCFVs). The new LCFV-based detector exploits multiorder features of the superpixels based on the Gaussian mixture model (GMM) and accordingly improves the discrimination capability between the ship targets and the sea clutter, especially in low SCR cases. Experimental results demonstrate that the proposed LCFV-based detection algorithm provides better detection performance than the commonly used detection algorithms. Numéro de notice : A2020-530 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2976880 date de publication en ligne : 18/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2976880 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95713 [article]

Improving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations / Guanxu Chen in Journal of geodesy, vol 94 n° 6 (June 2020)  

Public [article]  inJournal of geodesy > vol 94 n° 6 (June 2020) Titre : Improving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations Type de document : Article/Communication Auteurs : Guanxu Chen, Auteur ; Yang Liu, Auteur ; Yanxiong Liu, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] contrainte géométrique [Termes descripteurs IGN] fond marin [Termes descripteurs IGN] GNSS-Acoustique [Termes descripteurs IGN] navire [Termes descripteurs IGN] positionnement par GNSS [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] profondeur [Termes descripteurs IGN] station GNSS [Termes descripteurs IGN] trajectoire Résumé : (auteur) The position of a seafloor geodetic station can be determined by combining Global Navigation Satellite System (GNSS) and acoustic technologies, called GNSS-acoustic positioning. The precision of GNSS-acoustic positioning, a technique that employs the distance intersection, is determined by the positioning geometry formed by the ship’s track lines with respect to the seafloor station and the errors in the measurements. In the context of a shallow sea trial, we studied three key techniques in GNSS-acoustic positioning: the optimal geometric configuration, differencing techniques for acoustic observations and depth constraints offered by pressure gauges. The results showed that the optimal geometric configuration is a circular track with a radius of 2‾√ times the depth plus an overhead cross-track with a length of the circle diameter. Differenced observations can improve the horizontal positioning precision but will worsen the vertical positioning precision due to the change in the geometric configuration and the elimination of vertical information if the number of observations is limited. The proposed difference strategy, that is, applying a symmetric location difference operator to the circular track and an undifference operator to the cross-track, can effectively improve the horizontal precision and avoid vertical defects. By using relative depth observations from two pressure gauges as constraints, the vertical defects of GNSS-acoustic positioning can be improved, achieving a better vertical positioning precision. Applying the proposed methods to high-quality GNSS and acoustic observations, the positioning precision of a shallow seafloor geodetic station can be better than 2 cm. Numéro de notice : A2020-377 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern date de publication en ligne : 27/06/2020 En ligne : https://doi.org/10.1007/s00190-020-01389-1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95369 [article]

Validation of marine geoid models by utilizing hydrodynamic model and shipborne GNSS profiles / Sander Varbla in Marine geodesy, Vol 43 n° 2 (March 2020)  

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Geographies of maritime transport, Ch. 4. Geography versus topology in the evolution of the global container shipping network (1977-2016) / César Ducruet (2020)    

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IWV retrieval from shipborne GPS receiver on hydrographic ship Borda [diaporama] / Olivier Bock (2020)  

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Ship identification and characterization in Sentinel-1 SAR images with multi-task deep learning / Clément Dechesne in Remote sensing, Vol 11 n° 24 (December-2 2019)  

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Discriminating ship from radio frequency interference based on noncircularity and non-gaussianity in sentinel-1 SAR imagery / Xiangguang Leng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)  

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Ship Traffic Simulation to assess noise exposure of whale populations in Canada / Axel Orger (2017) 

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The Costa Concordia last cruise: The first application of high frequency monitoring based on COSMO-SkyMed constellation for wreck removal / Andrea Ciampalini in ISPRS Journal of photogrammetry and remote sensing, vol 112 (February 2016)  

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Improvement of GPS/acoustic seafloor positioning precision through controlling the ship’s track line / M. Sato in Journal of geodesy, vol 87 n° 9 (September 2013)  

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Study on the new methods of ship object detection based on GNSS reflection / Yong Lu in Marine geodesy, vol 36 n° 1 (January - March 2013)  

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