Abstract
The commercial drone market has substantially grown over the past few years. While providing numerous advantages in various fields and applications, drones also provide ample opportunities for misuse by irresponsible hobbyists or malevolent actors. The increasing number of safety/security incidents in which drones are involved has motivated researchers to find new and ingenious ways to detect, locate and counter this type of vehicles. In this paper, we propose a new method to detect frequency hopping spread spectrum - Gaussian frequency-shift keying (FHSS-GFSK) drone communication signals, in a non-cooperative scenario, where no prior information about the signals of interest is available. The system is designed to detect and retrieve data bit sequences through a compressive sampling approach, which includes the extraction of the reduced spectral information and a soft detection algorithm. The performance of the proposed approach is assessed in terms of bit error rate and compared with that of a Viterbi detector and a neural network-based detector. The effectiveness of the method described in the paper highlights the fact that current UAV communications are not infallible and present real security issues.
Highlights
U NMANNED aerial vehicles (UAVs), commonly known as drones, are readily available and easy to use
Unlike most previous research, which focuses on different aspects related to frequency hopping spread spectrum (FHSS) communications jamming [23], [26], [27], our paper proposes an approach to detect the FHSS-Gaussian frequency shift keying (GFSK) signals and recover the transmitted data bit sequences by eavesdropping on the communication between the UAV and its controller
A closely related research work [35], which is considered a reference throughout this paper, relies on a Viterbi sequence detector (VD) to recover the transmitted bits from compressively sampled FHSS-GFSK signals
Summary
U NMANNED aerial vehicles (UAVs), commonly known as drones, are readily available and easy to use. Unlike most previous research, which focuses on different aspects related to FHSS communications jamming [23], [26], [27], our paper proposes an approach to detect the FHSS-GFSK signals and recover the transmitted data bit sequences by eavesdropping on the communication between the UAV and its controller. A closely related research work [35], which is considered a reference throughout this paper, relies on a Viterbi sequence detector (VD) to recover the transmitted bits from compressively sampled FHSS-GFSK signals. Compared with the related research papers cited above, the proposed approach skips the signal reconstruction phase, and aims at directly detecting the sequences of bits transmitted by the drone controller.
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