DroneDetect Dataset: A Radio Frequency dataset of Unmanned Aerial System (UAS) Signals for Machine Learning Detection & Classification

Citation Author(s):
Carolyn J.
Swinney
University of Essex
John C.
Woods
University of Essex
Submitted by:
Carolyn Swinney
Last updated:
Tue, 05/17/2022 - 22:21
DOI:
10.21227/5jjj-1m32
Data Format:
Link to Paper:
License:
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Abstract 

The DroneDetect dataset consists of 7 different models of popular Unmanned Aerial Systems (UAS) including the new DJI Mavic 2 Air S, DJI Mavic Pro, DJI Mavic Pro 2, DJI Inspire 2, DJI Mavic Mini, DJI Phantom 4 and the Parrot Disco. Recordings were collected using a Nuand BladeRF SDR and using open source software GNURadio. There are 4 subsets of data included in this dataset, the UAS signals in the presence of Bluetooth interference, in the presence of Wi-Fi signals, in the presence of both and with no interference. 3 flight modes are captured - switched on, hovering and flying.

Instructions: 

Sample rate: 60Mbits/s

Bandwidth: 28MHz

Centre Freq: 2.4375GHz

Each recording consists of 1.2 x 10^8 complex samples equating to 2 seconds recording time. Data is saved into ‘.dat’ files  and the complex data is saved as interleaved floats. ‘load_data.py’ is included for the data to be loaded into python and further split into smaller samples 20ms in length.

Files are categorised by interference, then by flight mode –

Switched on = ON

Hovering = HO

Flying = FY

Each file name uses an interference identifier, 00 for a clean signal, 01 for Bluetooth only, 10 for Wi-Fi only and 11 for Bluetooth and Wi-Fi interference concurrently. An example file name for Mavic Mini switched on in the presence of Bluetooth and Wi-Fi interference would be:

MIN + 11 + 00 + 00 = MIN_1100_00.dat

Comments

Nice release, thanks for sharing the data! It will be useful for us by complementing our own "Radio-Frequency Control and Video Signal Recordings of Drones" (https://zenodo.org/record/4264467).

Submitted by Taneli Riihonen on Thu, 08/26/2021 - 04:22