AI Technologies for Drone Operations in Jamming Environments, step 2
| Reference number | |
| Coordinator | Wireless P2P Technologies AB |
| Funding from Vinnova | SEK 1 905 195 |
| Project duration | November 2025 - November 2026 |
| Status | Ongoing |
| Venture | Civil-military synergies |
Purpose and goal
The increasing use of unmanned platforms, such as drones, in modern conflicts is accompanied by a rise in countermeasures against Unmanned Aerial Systems (UAS), creating challenges in accessing the radio frequency spectrum. To effectively utilize allocated RF resources, drones must be capable of spectrum monitoring in complex operational environments, particularly by detecting intentional jamming of the frequencies they rely on.
Expected effects and result
The expected results are an increased efficiency and survivability of drones in jamming environments through the use of efficient and RF domain-aware machine learning techniques.
Planned approach and implementation
The project includes four phases: AP1, project management, runs from November 2025 to October 2026, with a mid-term evaluation and a final report. AP2 and AP3 focus on Proof-of-Concept for PASAD on SDR platform, and Classification of jamming and tactical integration, which will be carried out from November 2025 to August 2026. AP4, future work, identifies continued research on application of ML for robust operation in jamming environments, and will be completed with final report in October 2026.