AI-Based RF Signal Detection and Analysis of Enemy Communication Signals with Real-Time Battlefield Visualization

This study proposes a drone-mounted, AI-based wireless signal detection system that accurately localizes hostile radio emitters and visualizes results in real time. Using RSSI data collected in an open-field environment, path-loss modeling is performed via linear regression, numerical optimization, and machine learning. The resulting models generate range estimates, which are fused with trilateration to determine emitter locations. Experimental results demonstrate high localization accuracy, confirming the practical feasibility of real-time, drone-based signal detection and localization.