AI Technologies for Drone Operations in Jamming Environments

Purpose and goal: This project aims to carry out a feasibility study and field testing with using an existing cognitive radio platform based on Software-Defined Radio (SDR). The project will explore the application of advanced AI/ML algorithms to detect intentional jamming by technologically skilled adversaries. The focus is on

equipping drone users with advanced detection and identification capabilities to reduce drone losses and improve situational awareness in the RF domain. Expected results and effects:

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. Approach and implementation:

The project consists of four phases: AP1, project management, running from November 2024 to October 2025, with a mid-term evaluation and final report. AP2 and AP3 focus on the development and evaluation of ML-based interference detection on synthetic and real data, respectively, conducted from November 2024 to August 2025. AP4, future work, identifies continued research on the application of ML for robust drone operations in disrupted environments, concluding with a final report in October 2025.