The increasing complexity of military operations requires more advanced electronic warfare (EW) systems capable of dealing with multiple threats and operating in electromagnetic congested scenarios. Current solutions are partially effective and require the complex integration of different sensors and frequency bands. As a result, there is a growing need for automated EW systems that can rapidly identify and respond to threats, especially given the limited availability of qualified personnel.

To meet this challenge, this topic aims to further develop and integrate technologies to develop a more robust, cognitive and operational EW system. Cognitive EW systems that use AI and machine learning can detect, learn and interact with the environment, accelerating the development and implementation of next-generation EW threat detection, suppression and neutralisation technologies. These systems can interpret large amounts of data from multiple sources, operate autonomously and provide faster and better-quality data, ultimately automating system decisions and improving response time in critical situations.

Beyond defence technologies, this topic also contributes to the STEP objectives as defined in the STEP Regulation in the target investment area of deep and digital technologies.

Targeted types of activities: Studies and design, not excluding upstream and downstream activities eligible for development actions.

Indicative budget: EUR 24 000 000 for this topic under the EDF-2026-DA call.

Indicative number of proposals to be funded: One proposal is to be funded for this topic. However, depending on the quality of the proposals submitted and the budget available, more than one proposal may ultimately be funded for this topic.