DroneScale: drone load estimation via remote passive RF sensing

Phuc Nguyen, Vimal Kakaraparthi, Nam Bui, Nikshep Umamahesh, Nhat Pham, Hoang Truong, Yeswanth Guddeti, Dinesh Bharadia, Richard Han, Eric Frew, Daniel Massey, Tam Vu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

Drones have carried weapons, drugs, explosives and illegal packages in the recent past, raising strong concerns from public authorities. While existing drone monitoring systems only focus on detecting drone presence, localizing or fingerprinting the drone, there is a lack of a solution for estimating the additional load carried by a drone. In this paper, we present a novel passive RF system, namely DroneScale, to monitor the wireless signals transmitted by commercial drones and then confirm their models and loads. Our key technical contribution is a proposed technique to passively capture vibration at high resolution (i.e., 1Hz vibration) from afar, which was not possible before. We prototype DroneScale using COTS RF components and illustrate that it can monitor the body vibration of a drone at the targeted resolution. In addition, we develop learning algorithms to extract the physical vibration of the drone from the transmitted signal to infer the model of a drone and the load carried by it. We evaluate the DroneScale system using 5 different drone models, which carry external loads of up to 400g. The experimental results show that the system is able to estimate the external load of a drone with an average accuracy of 96.27%. We also analyze the sensitivity of the system with different load placements with respect to the drone's body, flight modes, and distances up to 200 meters.

Original languageEnglish
Title of host publicationSenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
Place of PublicationNew York, New York
PublisherAssociation for Computing Machinery, Inc
Pages326-339
Number of pages14
ISBN (Electronic)9781450375900
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020 - Virtual, Online, Japan
Duration: 16 Nov 202019 Nov 2020

Publication series

NameSenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems

Conference

Conference18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020
CountryJapan
CityVirtual, Online
Period16/11/2019/11/20

Keywords

  • drone load estimation
  • drone security
  • RF sensing systems

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