CARG AI4UAV: Detecting 5G-Enabled UAVs
The project aims to develop the following capabilities:
- Detecting and identifying UAS that use 5G/LTE control.
- Obtaining UAS location information.
- Real-time implementation of the system using 5G infrastructure and professional Graphical User Interface (GUI) for visualizing the detected objects on the map (situation awareness).
Milestones
- Develop software and hardware architecture for the integrated system and complete the software design.
- Simulations and Flight Data Collection
- Integration and Tech Demonstrations
Research Papers
- Kaza, K, Mehta, V, Azad, H, Bolic, M, Mantegh, I. An Intent Modeling and Inference Framework for Autonomous and Remotely Piloted Aerial Systems. arXiv preprint arXiv:2409.08472, 2024.
- - Description: An Intent Modeling and Inference Framework for Autonomous and Remotely Piloted Aerial Systems published in arXiv preprint arXiv:2409.08472.
- Zhai, Q., Bolic, M., Li, Y., Cheng, W., Liu, C.. A Q-Learning-Based Resource Allocation for Downlink Non-Orthogonal Multiple Access Systems Considering QoS. IEEE Access, 2021.
- - Description:
