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Article

Improved GNSS Localization and Byzantine Detection in UAV Swarms

1
Department of Mechanical Engineering, Ariel University, Ariel 4070000, Israel
2
Department of Industrial Engineering and Management, Ariel University, Ariel 4070000, Israel
3
Ariel Cyber Innovation Center, Ariel University, Ariel 4070000, Israel
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(24), 7239; https://doi.org/10.3390/s20247239
Received: 18 November 2020 / Revised: 13 December 2020 / Accepted: 14 December 2020 / Published: 17 December 2020
(This article belongs to the Special Issue Sensor for Autonomous Drones)
Many tasks performed by swarms of unmanned aerial vehicles require localization. In many cases, the sensors that take part in the localization process suffer from inherent measurement errors. This problem is amplified when disruptions are added, either endogenously through Byzantine failures of agents within the swarm, or exogenously by some external source, such as a GNSS jammer. In this paper, we first introduce an improved localization method based on distance observation. Then, we devise schemes for detecting Byzantine agents, in scenarios of endogenous disruptions, and for detecting a disrupted area, in case the source of the problem is exogenous. Finally, we apply pool testing techniques to reduce the communication traffic and the computation time of our schemes. The optimal pool size should be chosen carefully, as very small or very large pools may impair the ability to identify the source/s of disruption. A set of simulated experiments demonstrates the effectiveness of our proposed methods, which enable reliable error estimation even amid disruptions. This work is the first, to the best of our knowledge, that embeds identification of endogenous and exogenous disruptions into the localization process. View Full-Text
Keywords: FANET; UAV swarm; GNSS localization; Byzantine detection; pool testing FANET; UAV swarm; GNSS localization; Byzantine detection; pool testing
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MDPI and ACS Style

Hacohen, S.; Medina, O.; Grinshpoun, T.; Shvalb, N. Improved GNSS Localization and Byzantine Detection in UAV Swarms. Sensors 2020, 20, 7239. https://doi.org/10.3390/s20247239

AMA Style

Hacohen S, Medina O, Grinshpoun T, Shvalb N. Improved GNSS Localization and Byzantine Detection in UAV Swarms. Sensors. 2020; 20(24):7239. https://doi.org/10.3390/s20247239

Chicago/Turabian Style

Hacohen, Shlomi, Oded Medina, Tal Grinshpoun, and Nir Shvalb. 2020. "Improved GNSS Localization and Byzantine Detection in UAV Swarms" Sensors 20, no. 24: 7239. https://doi.org/10.3390/s20247239

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