About the Project

Mission

The mission is to improve awareness of sensor spoofing threats while developing a practical platform for neural network-based detection strategies in UAV systems. We are leveraging Unreal Engine 5 to create a high-fidelity simulation system that enables realistic sensor spoofing scenarios and provides a robust testing environment for AI-based detection algorithms.

This project builds upon Project AirSim, maintained by IAMAI Simulations — a team of former engineers from Microsoft’s original AirSim project. We’ve extended the platform significantly with custom scripts, libraries, and modifications to the Unreal Engine 5 integration to meet our specific simulation requirements. All credit for the base AirSim framework goes to IAMAI Simulations; our contributions include specialized sensor spoofing capabilities and detection systems developed in our forked repository.

Team

• Project Lead: Izzy Burley
• Systems & Architecture: Carl Holmberg
• Neural Networks & Edge Computing: Drew Schineller
• Simulation & Integration: Kush Parmar
• Hardware & Signal Processing: Will Field
• Embedded Systems & Communication: Sachel Jetly

Sponsor

This project is sponsored by a U.S. Navy-affiliated research partner focused on advancing low-cost UAV spoofing platforms and real-time spoof detection methods.

Scope

• Virtual sensor generation and spoof injection
• Embedded AI for real-time classification
• Emulated done flight and esting environments
• Modular system architecture for future research