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Optimizing Φ-Net Using TanDEM-X Bistatic Data for High-Resolution DEM Generation

Dell Amore, Luca and Soledade Matos Amorim, Vinícius and Rizzoli, Paola (2024) Optimizing Φ-Net Using TanDEM-X Bistatic Data for High-Resolution DEM Generation. In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR. European Conference on Synthetic Aperture Radar (EUSAR), 2024-04-23 - 2024-04-26, Munich, Germany. ISSN 2197-4403.

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Phi-Net is a deep residual learning architecture and is currently one of the most accurate state-of-the-art approaches for Synthetic Aperture Radar interferometric (InSAR) phase filtering and coherence estimation. The network has proven to outperform classical denoising strategies concerning the estimation of InSAR parameters and therefore is very suitable for the generation of high-resolution Digital Elevation Models (DEMs). However, some limitations are shown over critical areas characterized by low signal-to-noise ratio (SNR) or by geometric distortions, i.e. shadow and layover. There, Phi-Net wrongly reconstructs the InSAR phase and inserts artefacts, thus leading to an unreliable input for typical phase unwrapping algorithms. Moreover, being trained with synthetic data only, there is still potential for an optimization which is closely related to the patterns that can be found in real InSAR data. In this paper we propose a preliminary analysis which exploits TanDEM-X bistatic data in order to optimize and fine tune Phi-Net. In particular, we address the problem of removing artefacts in the filtered InSAR phase and improving the estimation performance, which would allow for the generation of a more accurate and reliable unwrapped phase and higher-precision DEMs.

Item URL in elib:https://elib.dlr.de/197748/
Document Type:Conference or Workshop Item (Speech)
Title:Optimizing Φ-Net Using TanDEM-X Bistatic Data for High-Resolution DEM Generation
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Dell Amore, LucaUNSPECIFIEDhttps://orcid.org/0000-0002-6731-1300UNSPECIFIED
Rizzoli, PaolaUNSPECIFIEDhttps://orcid.org/0000-0001-9118-2732UNSPECIFIED
Date:April 2024
Journal or Publication Title:Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:SAR, SAR Interferometry (InSAR), Phi-Net, InSAR phase denoising
Event Title:European Conference on Synthetic Aperture Radar (EUSAR)
Event Location:Munich, Germany
Event Type:international Conference
Event Dates:2024-04-23 - 2024-04-26
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - AI4SAR
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > Spaceborne SAR Systems
Deposited By: Dell Amore, Luca
Deposited On:09 Oct 2023 08:47
Last Modified:15 Feb 2024 10:15

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