Locating multiple GPS jammers using networked UAVs

Sriramya Bhamidipati, Grace Xingxin Gao

Research output: Contribution to journalArticle

Abstract

Recent technologies, such as, Internet of Things and cloud services, increases the usage of small and low-cost networked unmanned aerial vehicles (UAVs), which needs to be robust against malicious global positioning system (GPS) attacks. Due to the availability of low-cost GPS jammers in the commercial market, there has been a rising risk of multiple jammers and not just one. However, it is challenging to locate multiple jammers because the traditional jammer localization via multilateration is applicable for only a single jammer case. Also, during a jamming attack, the positioning capability of an on-board GPS receiver is compromised given its inability to track GPS signals. We propose a simultaneous localization of multiple jammers and receivers (SLMR) algorithm by analyzing the variation in the front-end signal power recorded by the GPS receivers on-board a network of UAVs. Our algorithm not only locates multiple jammers but also utilizes these malicious sources as additional navigation signals for positioning the UAVs. We design a Gaussian mixture probability hypothesis density filter over a graph framework, which is optimized using a Levenberg-Marquardt minimizer. Using a simulated experimental setup, we validate the convergence and localization accuracy of our SLMR algorithm for various cases, including attacks with a single jammer, multiple jammers, and a varying number of jammers. We also demonstrate that our SLMR algorithm is able to simultaneously locate multiple jammers and UAVs, even for a larger transmitted power of the jammers.

Original languageEnglish (US)
Article number8629980
Pages (from-to)1816-1828
Number of pages13
JournalIEEE Internet of Things Journal
Volume6
Issue number2
DOIs
StatePublished - Apr 2019

Fingerprint

Unmanned aerial vehicles (UAV)
Global positioning system
Jamming
Costs
Navigation
Availability

Keywords

  • Graph optimization
  • Internet of Things (IoT)
  • localization
  • multiple jammers
  • probability hypothesis density (PHD)
  • unmanned aerial vehicles (UAVs)

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Cite this

Locating multiple GPS jammers using networked UAVs. / Bhamidipati, Sriramya; Gao, Grace Xingxin.

In: IEEE Internet of Things Journal, Vol. 6, No. 2, 8629980, 04.2019, p. 1816-1828.

Research output: Contribution to journalArticle

Bhamidipati, Sriramya ; Gao, Grace Xingxin. / Locating multiple GPS jammers using networked UAVs. In: IEEE Internet of Things Journal. 2019 ; Vol. 6, No. 2. pp. 1816-1828.
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