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Similarity criterion for SAR tomography over dense urban area

  • Clement Rambour
  • , Loic Denis
  • , Florence Tupin
  • , Jean Marie Nicolas
  • , Helene Oriot
  • , Laurent Ferro-Famil
  • , Charles Deledalle
  • Université Paris-Saclay
  • CNRS
  • ONERA Office National d'Etudes et Recherches Aerospatiales
  • University of Rennes

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

Résumé

Starting from a stack of co-registered SAR images in interferometric configuration, SAR tomography performs a reconstruction of the reflectivity of scatterers in 3-D. Several scatterers observed within the same resolution cell of each SAR image can be separated by jointly unmixing the SAR complex amplitude observed throughout the stack. To achieve a reliable tomographic reconstruction, it is necessary to estimate locally the SAR covariance matrix by performing some spatial averaging. This necessary averaging step introduces some resolution loss and can bias the tomographic reconstruction by mistakenly including the response of scatterers located within the averaging area but outside the resolution cell of interest. This paper addresses the problem of identifying pixels corresponding to similar tomographic content, i.e., pixels that can be safely averaged prior to tomographic reconstruction. We derive a similarity criterion adapted to SAR tomography and compare its performance with existing criteria on a stack of Spotlight TerraSAR-X images.

langue originaleAnglais
titre2017 IEEE International Geoscience and Remote Sensing Symposium
Sous-titreInternational Cooperation for Global Awareness, IGARSS 2017 - Proceedings
EditeurInstitute of Electrical and Electronics Engineers Inc.
Pages1760-1763
Nombre de pages4
ISBN (Electronique)9781509049516
Les DOIs
étatPublié - 1 déc. 2017
Modification externeOui
Evénement37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 - Fort Worth, États-Unis
Durée: 23 juil. 201728 juil. 2017

Série de publications

NomInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2017-July

Une conférence

Une conférence37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Pays/TerritoireÉtats-Unis
La villeFort Worth
période23/07/1728/07/17

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