DroneRF dataset: A dataset of drones for RF-based detection, classification, and identification

Published: 2 March 2019| Version 1 | DOI: 10.17632/f4c2b4n755.1
, Amr Mohamed,


DroneRF dataset: a radio frequency (RF) based dataset of drones functioning in different modes, including off, on and connected, hovering, flying, and video recording. The dataset contains recordings of RF activities, composed of 227 recorded segments collected from 3 different drones, as well as recordings of background RF activities with no drones. The data has been collected by RF receivers that intercepts the drone’s communications with the flight control module. The receivers are connected to two laptops, via PCIe cables, that runs a program responsible for fetching, processing and storing the sensed RF data in a database. The dataset can be used in drone detection, drone identification and drone tracking.


Steps to reproduce

The complete code to reproduce the dataset can be accessed in the related link below. To visualize the data, various software can be used. As mentioned before, each flight mode recording is composed of segments, each segment is split into two parts. In order to plot a segment, the two parts should be loaded into the software work-space together (E.g. 11000L_3, 11000H_3). After loading the data, the data can be normalized between 1 and -1 for a better visualization.


Qatar University


Artifact Detection, Drone (Aircraft), Radio Frequency Measurement