Work

Extending InSAR2InSAR to Sentinel-1 Data

Year: 2025

Type: article

Abstract: Interferometric SAR parameters estimation is a very important and challenging problem. The InSAR2InSAR method previously proposed is one of the few self-supervised methods that 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 Swath mode possess the necessary properties to train and apply InSAR2InSAR effectively. In this paper, we demonstrate the ability of InSAR2InSAR to process across-track Sentinel-1 interferometric images with state-of-the-art performances.

Source: IEEE Geoscience and Remote Sensing Letters

DOI: 10.1109/lgrs.2025.3558363

Authors: Carla Geara, Colette Gelas, Louis de Vitry, Elise Colin, Florence Tupin

Institutions: Université Paris-Saclay, Office National d'Études et de Recherches Aérospatiales, Institut Polytechnique de Paris, Laboratoire Traitement et Communication de l’Information

Language: English

Topic: Synthetic Aperture Radar (SAR) Applications and Techniques

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: Association Nationale de la Recherche et de la Technologie

OpenAlex ID: W4409225812