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A synchronization algorithm for spaceborne/stationary BiSAR imaging based on contrast optimization with direct signal from radar satellite / M. Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 4 (April 2016) . - pp 1977 - 1989 Titre : A synchronization algorithm for spaceborne/stationary BiSAR imaging based on contrast optimization with direct signal from radar satellite Type de document : Article/Communication Auteurs : M. Zhang, Auteur ; Robert Wang, Auteur ; Y. Deng, Auteur Année de publication : 2016 Article en page(s) : pp 1977 - 1989 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] amélioration du contraste [Termes IGN] image radar moirée [Termes IGN] optimisation (mathématiques) [Termes IGN] radar bistatique [Termes IGN] synchronisation Résumé : (Auteur) This paper proposes a synchronization algorithm for bistatic synthetic aperture radar (BiSAR) imaging in a spaceborne/stationary configuration. In real bistatic systems, synchronization errors are generally introduced into the received data. Additionally, the lack of precise imaging parameters, such as the position of the transmitter and the accurate sampling time, could affect the imaging quality greatly. Fortunately, the image could be well focused by the proposed algorithm in the case of lack of the accurate position of a transmitter and the sampling time. First, a preprocessing step is employed to remove synchronization errors through matching an echo signal with a direct signal. Then, a modified chirp scaling factor containing an error phase term is constructed, and the accurate position of the transmitter and the sampling time can be acquired by the phase extraction of the direct signal and the searching method based on contrast optimization. After that, the corresponding imaging process can be implemented. Finally, the proposed algorithm is validated by the simulation and experimental results, where TerraSAR-X is used as the illuminator. Numéro de notice : A2016-837 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2493078 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2493078 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82881 [article]

DEM resolution dependencies of terrain attributes across a landscape / Y. Deng in International journal of geographical information science IJGIS, vol 21 n° 1-2 (january 2007)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 21 n° 1-2 (january 2007) . - pp 187 - 213 Titre : DEM resolution dependencies of terrain attributes across a landscape Type de document : Article/Communication Auteurs : Y. Deng, Auteur ; B.O. Bauers, Auteur ; J.P. Wilson, Auteur Année de publication : 2007 Article en page(s) : pp 187 - 213 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse de groupement [Termes IGN] attribut géomètrique [Termes IGN] classification non dirigée [Termes IGN] corrélation [Termes IGN] échantillonnage d'image [Termes IGN] limite de résolution géométrique [Termes IGN] modèle numérique de surface [Termes IGN] régression [Termes IGN] relief Résumé : (Auteur) This paper documents resolution dependencies in terrain analysis and describes how they vary across landform location. Six terrain attributes were evaluated as a function of DEM resolution—slope, plan curvature, profile curvature, north–south slope orientation, east–west slope orientation, and topographic wetness index. The research highlights the effect of varying spatial resolution through a spatial sampling/resampling scheme while maintaining sets of indexed sample points at various resolutions. Tested sample points therefore coincide exactly between two directly compared resolutions in terms of their location and elevation value. An unsupervised landform classification procedure based on statistical clustering algorithms was employed to define landform classes in a reproducible manner. Correlation and regression analyses identified sensitive and consistent responses for each attribute as resolution was changed, although the tested terrain attributes responded in characteristically different ways. These responses displayed distinguishable patterns among various landform classes, a conclusion that was further verified by a series of two-sample, two-tailed t-tests. Copyright Taylor & Francis Numéro de notice : A2007-032 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810600894364 En ligne : https://doi.org/10.1080/13658810600894364 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28398 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-07011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-07012	RAB	Revue	Centre de documentation	En réserve L003	Disponible