IDENTIFYING AND ANALYZING DJI DRONE SIGNALS

Abstract

The widespread use of drones in commercial, industrial, military and security applications has led to a growing need for techniques to analyse their signals. Understanding the communication signals of drones is essential for applications such as airspace monitoring, counter-unmanned aerial vehicles technologies and electronic warfare. This defines the topicality of the topic. That is why the purpose of the study focuses on the identification and analysis of DJI drone signals using software defined radio. The research aims to find their frequencies usage, look for the drone activities in spectrogram, record them and characterize modulation types of drones, specifically the DJI Air 3 and Phantom 4. The working methods are based on using HackRF One software defined radio alongside the DragonOS operating system and HackRF Spectral Analyzer, SDR++ and Inspectrum software. Signal identification is performed in controlled urban and non-urban environments, allowing for the examination of telemetry signal. Different signal processing techniques are used including spectral analysis and modulation classification are applied to identify DJI drone ID. By analysing frequency bands, bandwidth requirements, and transmission structures, the study indicates how both drones communicate and adapt to environmental factors such as interference. Main conclusions from this paper are revealing that DJI drones use frequency hopping, orthogonal frequency division multiplexing modulation adapting itself with quadrature phase shift keying, 16 and 64 quadrature amplitude modulation depending on the enviroment. They also use Zadoff-Chu sequencies for synchronizing their drone ID packets. Having in mind this, the signal width and strength also chages based on the urban or no-urban environments that the drone is.