SDR-Captured Drone Controller LoRa Spectrogram Dataset

Published: 1 June 2026| Version 1 | DOI: 10.17632/7j8tf5k677.1
Contributors:
Gennadii Dudarek,
,

Description

This dataset contains spectrograms of drone controllers captured during non-cooperative drone operations and can be used for testing detection algorithms such as YOLO. The hardware setup: - TX12 Mark II radio controller (RC), and a Nomad Dual Gemini Xrossband ExpressLRS Module. - The 30dB attenuator was plugged in to the RC antenna to decrease the power of the control signal. - FPV drone equipped with a BAYCKRC 900/2400 Dual Band Gemini RX receiver - ADALM-Pluto SDR RevC - Panel Antenna - Apple M2 Max MacBook Pro laptop Both the transmitter and receiver are compatible with ExpressLRS 3.5.4 firmware and are equipped with dual 3rd-generation Semtech LR1121 transceivers. Software and settings: - MATLAB R2024b with Communications Toolbox Support Package - SDR sampling rate: 32 MHz - RC ELRS control bands: 2.4 GHz and 915 MHz - RC packet rates: 50 kHz and 100 kHz for both bands. Result: - LoRa packets with (500, 7-8) and (812, 7-8) bandwidth, spreading factor (BW, SF) parameters

Files

Steps to reproduce

For detailed guidance on steps to reproduce and usage please refer to our related works: [1] G. Dudarek and S. Martyniuk, “Identifying LoRa parameters using convolutional neural networks,” Radioelectronics and Communications Systems, Oct. 2025, doi: 10.20535/S0021347025020013. [2] G. Dudarek and S. Martyniuk, “From Discrete to Continuous LoRa Parameter Estimation Us-ing Vision-Based Deep Learning,” 2026, Submission is in progress.

Categories

Radio, Object Detection, Chirped Signal, Drone (Aircraft)

Licence