Rizzoli, Paola and Carcereri, Daniel and Becker Campos, Alexandre and Gollin, Nicola and Dell'Amore, Luca and Ghio, Federico and Bueso Bello, Jose Luis and Gonzalez, Carolina and Martone, Michele and Zink, Manfred (2026) AI4TDX: How can AI leverage the exploitation of TanDEM-X data to jointly benefit science and shape future mission concepts? In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR. European Conference on Synthetic Aperture Radar (EUSAR), 2026-06-08 - 2026-06-11, Baden-Baden, Germany. ISSN 2197-4403.
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Abstract
Over the past 15 years, TanDEM-X has demonstrated its groundbreaking potential, setting a new standard in digital elevation model (DEM) products based on single-pass synthetic aperture radar interferometry (InSAR) and establishing itself as a milestone for Earth Observation (EO). Beyond its success in DEM generation, the mission has also proven to be of enormous value for scientific applications, enabling novel insights across a wide range of disciplines. When combined with artificial intelligence (AI), TanDEM-X offers even greater opportunities, both to support the scientific community through enhanced data analysis and interpretation, and to drive the development of future mission concepts. The synergy between AI and bistatic InSAR configurations holds immense potential, especially when leveraged in a physics-informed manner rather than considering AI as a mere black box. This paper presents a summary of ongoing activities at the Radar Science Group of the DLR Microwaves and Radar Institute that integrate AI with TanDEM-X, aiming to improve performance and extract valuable insights at all stages of the SAR processing chain, from raw data handling to high-level scientific applications. The results highlight how the intelligent fusion of AI and bistatic radar techniques can unlock new levels of efficiency, accuracy, and scientific understanding, paving the way for the design and optimization of future SAR mission concepts.
| Item URL in elib: | https://elib.dlr.de/223577/ | ||||||||||||||||||||||||||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||||||||||||||||||||||||||||||
| Title: | AI4TDX: How can AI leverage the exploitation of TanDEM-X data to jointly benefit science and shape future mission concepts? | ||||||||||||||||||||||||||||||||||||||||||||
| Authors: |
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| Date: | 2026 | ||||||||||||||||||||||||||||||||||||||||||||
| Journal or Publication Title: | Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR | ||||||||||||||||||||||||||||||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||||||||||||||||||||||||||||||
| Open Access: | No | ||||||||||||||||||||||||||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||||||||||||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||||||||||||||||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||||||||||||||||||||||||||||||
| ISSN: | 2197-4403 | ||||||||||||||||||||||||||||||||||||||||||||
| Status: | Accepted | ||||||||||||||||||||||||||||||||||||||||||||
| Keywords: | AI4SAR, TanDEM-X, Deep Learning, AI | ||||||||||||||||||||||||||||||||||||||||||||
| Event Title: | European Conference on Synthetic Aperture Radar (EUSAR) | ||||||||||||||||||||||||||||||||||||||||||||
| Event Location: | Baden-Baden, Germany | ||||||||||||||||||||||||||||||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||||||||||||||||||||||||||||||
| Event Start Date: | 8 June 2026 | ||||||||||||||||||||||||||||||||||||||||||||
| Event End Date: | 11 June 2026 | ||||||||||||||||||||||||||||||||||||||||||||
| Organizer: | VDE | ||||||||||||||||||||||||||||||||||||||||||||
| 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 Microwaves and Radar Institute > Spaceborne SAR Systems | ||||||||||||||||||||||||||||||||||||||||||||
| Deposited By: | Rizzoli, Paola | ||||||||||||||||||||||||||||||||||||||||||||
| Deposited On: | 15 Apr 2026 12:41 | ||||||||||||||||||||||||||||||||||||||||||||
| Last Modified: | 15 Apr 2026 12:41 |
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