CARDINAL RF (CARDRF): An Outdoor UAV/UAS/DRONE RF Signals with Bluetooth and WiFi Signals Dataset
Lead Experimenter
Olusiji Medaiyese and Adrian Lauf, University of Louisville
Link to Dataset
- Dataset Link: [IEEE Dataport]
Equipment and Software Used
Keysight High-Sampling Oscilloscope, drones, remote controllers from different vendors, WiFi and Bluetooth interferers (this is a BYOD experiment)
Description
The dataset contains UAV (telemetry and control), Bluetooth, and WiFi RF signals in .mat format. It was captured in an outdoor setting. Each RF signal has 5 million sampling points and spans a time period of 0.25ms. The script for plotting the signal is called SIGNAL_PLOT.mlx (a Matlab script) in the code zip file.
Publications
- O. O. Medaiyese, M. Ezuma, A. P. Lauf and A. A. Adeniran, "Hierarchical Learning Framework for UAV Detection and Identification," in IEEE Journal of Radio Frequency Identification, vol. 6, pp. 176-188, 2022, doi: 10.1109/JRFID.2022.3157653.
- O. O. Medaiyese, M. Ezuma, A. P. Lauf and I. Guvenc, "Semi-supervised Learning Framework for UAV Detection," in Proc. IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), pp. 1185-1190, Sep. 2021.
- O.O. Medaiyese, M. Ezuma, A.P. Lauf, and I. Guvenc, "Wavelet transform analytics for RF-based UAV detection and identification system using machine learning", Pervasive and Mobile Computing, 82, vol. 82, p.101569, June 2022.
Representative Results
- Result figures
The image below shows the data collection procedure and representative results on UAV/WiFi/Bluetooth classification accuracy.
Potential use cases for this dataset include:
- Interference Analysis and Mitigation
- UAV Identification and Classification