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DroneRFb-Spectra: A RF spectrogram dataset for drone recognition
- Citation Author(s):
- Submitted by:
- Ningning Yu
- Last updated:
- Fri, 11/08/2024 - 08:18
- DOI:
- 10.21227/wv7h-sv64
- Data Format:
- Research Article Link:
- License:
675 Views- Categories:
- Keywords:
Abstract
To develop radio frequency-based drone recognition, we release an RF spectrogram dataset, named DroneRFb-Spectra. All signals of drones were collected by a Universal Software Radio Peripheral (USRP) device, recording three Industrial Scientific Medical (ISM) bands under urban scenarios. The classes cover 7 common brands, i.e., DJI, Vbar, FrSky, Futaba, Taranis, RadioLink, and Skydroid, with a total number of 14460. Each spectrogram has been downsampled to the size of 512x512 from the original IQ data with a length of 50ms by using the short-time Fourier transform.
This dataset helps learn the characteristics of common drone RF signals, such as frequency, duration, and interval. Based on signal processing and deep learning, this dataset is used to develop and study novel drone recognition methods or models.
This dataset is related to the following paper as
N. Yu, J. Wu, C. Zhou, Z. Shi, and J. Chen, "Open Set Learning for RF-Based Drone Recognition via Signal Semantics," in IEEE Transactions on Information Forensics and Security, vol. 19, pp. 9894-9909, 2024, doi: 10.1109/TIFS.2024.3463535.
If you want to promote, publicize, or do academic research with this dataset, please cite the above-mentioned paper.
Documentation
| Attachment | Size |
|---|---|
 readme.txt | 752 bytes |
Comments
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Great work!
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