Artificial intelligence for Real-time Guidance of Onboard SAR applicationscore
ARGOS · Horizon Europe grant · 2026-06-01–2029-05-31
EC contribution
Total cost
Beneficiaries
About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-CL4-2025-02 · scheme HORIZON-RIA · topic HORIZON-CL4-2025-02-SPACE-31. CORDIS record →
Objective
Spaceborne Earth Observation (EO) systems are critical to addressing Europe’s environmental and security challenges, from climate change monitoring and disaster response to border surveillance and situational awareness. Synthetic Aperture Radar (SAR) satellites are particularly valuable given their ability to capture data independent of weather or lighting conditions. However, the complexity of SAR signals, the computational demands of image formation, and the limited resources of spaceborne platforms hinder the deployment of advanced onboard applications. To overcome these bottlenecks, the ARGOS project will develop a novel end-to-end Artificial Intelligence (AI) framework enabling high-level SAR applications directly from raw data onboard satellites.The project will design a unified onboard processing chain capable of handling SAR raw data and delivering near real-time application-specific inferences in different fields. To make these processes viable in the constrained space environment, ARGOS will focus on optimizing deep learning models, applying multi-tasking and Tiny AI approaches to reduce computational load and power consumption. The framework will be validated on representative space-qualified hardware, ensuring that the solutions can operate effectively under realistic resources. In parallel, the AI-driven approach will be benchmarked against state-of-the-art onboard SAR processing methods. The project will also demonstrate its versatility through demonstration scenarios, including maritime situational awareness, critical areas identification, and environmental monitoring.ARGOS will advance Europe’s autonomy in intelligent EO capabilities, enabling faster, more efficient, and resilient responses to environmental and geopolitical challenges. Ultimately, the project will bridge the gap between algorithmic innovation and operational deployment, serving both environmental and security needs while reinforcing Europe’s leadership in space-based intelligence.
Beneficiaries (9)
| Organisation | Country | Role | EC contribution | SME |
|---|---|---|---|---|
| DEUTSCHES ZENTRUM FUR LUFT - UND RAUMFAHRT EV | DE | coordinator | €579,993 | |
| ACCADEMIA EUROPEA DI BOLZANO | IT | participant | €349,927 | |
| UNIBAP SPACE SOLUTIONS AB (PUBL) | SE | participant | €300,000 | Yes |
| INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE | FR | participant | €190,000 | |
| TECHNISCHE UNIVERSITEIT DELFT | NL | participant | €160,067 | |
| ENVEO ENVIRONMENTAL EARTH OBSERVATION INFORMATION TECHNOLOGY GMBH | AT | participant | €130,130 | Yes |
| INSTITUTO NACIONAL DE TECNICA AEROESPACIAL ESTEBAN TERRADAS | ES | participant | €130,000 | |
| Marble Imaging GmbH | DE | participant | €80,091 | Yes |
| UNIVERSITATEA NATIONALA DE STIINTASI TEHNOLOGIE POLITEHNICA BUCURESTI | RO | participant | €80,015 |
Get the EU Defence Funding Calendar — free
The full calendar of open EU defence and dual-use funding calls, sorted by deadline, updated nightly. Delivered with DFM Analysis, our weekly briefing on who is funding what in European defence.
Or browse all open defence & dual-use calls on the funding calendar →
Defence Finance Monitor is an analytical and informational product. Grant data is official CORDIS; the paid Annual Professional subscription is handled on DFM Analysis.