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Extending InSAR2InSAR to Sentinel-1 Data

  • Carla Geara
  • , Colette Gelas
  • , Louis de Vitry
  • , Elise Colin
  • , Florence Tupin
  • Kanop (RAIL SAS)
  • Institut Polytechnique de Paris
  • Université Paris-Saclay

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

Résumé

Interferometric synthetic aperture radar (SAR) parameters’ estimation is a very important and challenging problem. The InSAR2InSAR method previously proposed is one of the few self-supervised methods which aims to estimate InSAR parameters. This method has proven to outperform state-of-the-art methods on simulated synthetic data. However, it has to be extended on real data. In this letter, we demonstrate that Sentinel-1 images acquired in the interferometric wide (IW) swath mode possess the necessary properties to train and apply InSAR2InSAR effectively. In this letter, we demonstrate the ability of InSAR2InSAR to process across-track Sentinel-1 interferometric images with state-of-the-art performances.

langue originaleAnglais
Numéro d'article4008105
journalIEEE Geoscience and Remote Sensing Letters
Volume22
Les DOIs
étatPublié - 1 janv. 2025

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