Problem

Rapid developments in the unmanned aerial systems (UAS) have made its usage in a variety of applications especially in military, high priority and sensitive government sites. The ability to accurately classify over-the-air radio signals will provide insights into spectrum utilization, device fingerprinting and protocol identification These insights can help the Warfighter to constantly be informed about adversaries transmitters capabilities without their knowledge. Recently, few researches have proposed feature-based machine learning techniques to classify RF signals. However, these researches are mostly evaluated on simulated environments, less accurate, and failed to explore advance machine learning techniques.