Advanced AI-Driven Detection and Localization of RF Emissions Using Software Defined Radios (SDRs)

This project focuses on utilizing Software Defined Radios (SDRs) for real-time RF data access and analysis in wireless channels, leveraging AI to interpret the statistical features of encrypted wireless signals (e.g., WiFi, Bluetooth, LTE). By combining SDR technology with advanced antennas and edge AI, the project aims to develop an integrated system for detecting, identifying, and localizing RF emissions.

The system will enhance signal detection and classification accuracy through machine learning and optimize real-time performance with minimal computing power. The research methodology includes innovative approaches such as advanced antenna designs, edge AI deployment, and precise localization techniques, ensuring flexibility, reduced latency, and improved decision-making.

This project aligns with several EPSRC strategic priorities, including the Digital Economy, Engineering, ICT, AI, and Security. By advancing the understanding and management of the wireless spectrum, it contributes to the development of secure, efficient digital infrastructures. The integration of SDRs and advanced antenna concepts represents significant engineering innovation, while AI-driven signal processing and classification align with EPSRC's AI research goals.

The ability to detect, identify, and localize RF emissions enhances cybersecurity and resilience in communication networks, demonstrating practical applications in fields such as cybersecurity, spectrum monitoring, and signal intelligence.