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Date

MYRIAD, the new European Defence Fund initiative revolutionizing satellite imagery analysis for defense

19/03/2026
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A 48-month European initiative combining artificial intelligence and satellite data to enhance surveillance and defense capabilities

MYRIAD will bring together nine European partners to develop advanced multi-source satellite imagery analysis technologies and strengthen EU technological sovereignty

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The MYRIAD research project (Multi-source information sYstem based on Remote sensing aI Analytics to support the strategic Defence domain), funded by the European Defence Fund, has officially commenced, bringing together a European consortium with the objective of developing advanced multi-source satellite imagery analysis technologies using artificial intelligence for strategic defense applications.

With a planned duration of 48 months and a total budget of nearly €5 million, MYRIAD is being developed by a consortium of nine European partners coordinated by GMV, involving leading organizations in applied research, artificial intelligence, space technologies, and geospatial analysis.

The project, which addresses a European technological challenge and seeks to improve the accuracy, speed, and reliability of analyses for defense applications through satellite imagery analysis, will be developed over four annual innovation cycles. During these cycles, a group of experts from European Ministries of Defence will provide feedback to ensure that the technological solutions are useful in real-world operations and can be deployed within the infrastructure of the European Union Satellite Centre (SatCen).

To achieve this, MYRIAD will focus on three key areas: development of advanced optical and radar imagery analysis technologies using artificial intelligence, evaluation and validation of their performance, and operational demonstrations with end-users to ensure effectiveness and relevance in real-world scenarios.

As project coordinator, GMV leads overall management, feasibility studies, and technical specification definition, as well as implementation of solutions through a workflow that will enable activation of analytical modules based on input data during various test campaigns.

The remaining consortium partners contribute key complementary capabilities, including expertise in compact space sensors and radiometric calibration, artificial intelligence algorithm and data analysis development, real-time processing and secure communications, multi-sensor data fusion tools, analytical workflow integration, and creation of datasets for AI model training.
 

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Strategic importance for European defense

Analysis of satellite imagery from various Earth observation space missions is a key element for strengthening intelligence, surveillance, and reconnaissance capabilities, as it enables detection and monitoring of activities even under adverse conditions such as bad weather, darkness, or camouflage. The combination of different sensors increases system resilience, improves interoperability between Member States, and enables full exploitation of artificial intelligence potential for processing large data volumes.

Furthermore, MYRIAD will contribute to strengthening European technological sovereignty by reducing dependence on non-European technologies in strategic domains such as geospatial intelligence and automated analysis. The project will drive the development of European standards for artificial intelligence use in defense and foster collaboration between industry, research centers, and institutional users, enhancing the competitiveness and industrial autonomy of the European space ecosystem.

Benefits for end users

Technologies developed within MYRIAD will enable improved quality and reliability of object analysis in defense applications through fusion of data from multiple satellite sources, reducing false positives and negatives and increasing result accuracy.

The project will also contribute to greater transparency and traceability in artificial intelligence use, facilitating analysts' understanding of how algorithms reach certain conclusions and enabling review of processes to minimize biases and errors. A significant reduction in manual workload for repetitive tasks is also expected, accelerating analysis times and improving continuous surveillance capabilities for critical areas.

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This document has been prepared in the framework of a project funded by the European Defence Fund (EDF). The views and opinions expressed in this document are those of the author(s) only and do not necessarily reflect those of the European Union or the granting authority. Neither the European Union nor the granting authority can be held responsible for any use that may be made of the information contained herein.

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