Florida International University engineers develop passive drone detection system

Researchers at Florida International University have developed a low-cost, passive detection method designed to identify small unmanned aircraft (micro-UAS) by sensing the extremely low-frequency (ELF) magnetic fields produced by their electric motors.

Unlike traditional radar, which transmits active radio signals, or acoustic systems that can be obscured by environmental noise, this system operates silently by capturing ambient electromagnetic signatures. Using a specialized receiver antenna and machine learning models, the technology analyzes the distinct magnetic patterns created by different motor geometries and electrical layouts. This allows the system to not only detect the presence of a drone but also identify its specific make and model.

In field trials published in the IEEE Sensors Journal, the system achieved an accuracy rate of 98.52% in outdoor settings at ranges of up to 15 meters. While the hardware is highly cost-effective, costing only a few hundred dollars to assemble, researchers noted that the current detection range remains a limitation for large-scale outdoor applications.