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.

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

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GPS spoofing and jamming are common attacks against the UAV, however, conducting these experiments for research can be difficult in many areas. This dataset consists of a logs from a benign flight as well as one where the UAV experiences GPS spoofing and jamming. The Keysight EXG N5172B signal generator is used to provide the true coordinates as a location in Shanghai, China.

Instructions: 

PX4 Autopilot v1.11.3 (https://px4.io) is used for all experiments, running on Pixhawk 4 flight controller (PX4_FMU_V5) and Pixhawk GPS receiver. The UAV frame is the Holybro S500. QGroundControl (v4.0.9) is used for GCS (http://qgroundcontrol.com). 

Full flight data is contained in ULOG files (https://dev.px4.io/v1.9.0/en/log/ulog_file_format.html)

CSV files are obtained by conversion using the ulog2csv script (https://github.com/PX4/pyulog/blob/master/pyulog/ulog2csv.py)

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The dataset contains measurement results of Radar Cross Section of different Unmanned Aerial Vehicles at 26-40 GHz. The measurements have been performed fro quasi-monostatic case (when the transmitter and receiver are spatially co-located) in the anechoic chamber. The data shows how radio waves are scattered by different UAVs at the specified frequency range.

 

 

Instructions: 

Some of DJI, Walkera, Parrot and Kyosho drones were measured.

The data is in ".csv" format. Each file contains the following information: frequency, theta, phi, and RCS.

The RCS signatures of the following drone models are available:

-DJI Phantom 4 Pro

-DJI F450

-DJI Mavic Pro

-Helicopter Kyosho

-Parrot AR.drone

-DJI Matrice M100

-Walkera Voyager 4

-Custom built hexacopter

-Tricopter HMF600, frame only

Polarization is mentioned in the file name:

  • HH - horizontal polarisation of the transmitter and the receiver

  • HV/VH - horizontal and vertical or vice versa

  • VV - vertical polarization of the transmitter and the receiver

In addition, 6S LiPo battery RCS is available.

 

 Published article can be found at: https://ieeexplore.ieee.org/document/9032332

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