Tackling the GNSS jamming problem using a particle filter algorithm

Roi Yozevitch, Boaz Ben Moshe, Sergei Safrigin

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

Abstract

GNSS Jammers are devices that generate RF noise in the carrier frequency of the GNSS (e.g., 1.57Ghz for L1 GPS). Jamming behavior can be characterized by a sharp degradation in the SNR of the GNSS satellites. In this paper we suggest a Bayesian particle filter approach for jamming detection and localization using crowd-sourcing of Smart-Phones GNSS data. The presented algorithm computes in real-time a probabilistic map of the jammers' positions. Since a 2D histogram distribution space is generated, multiple jammers can be detected simultaneously. The presented algorithm can cope with various types of jammers - no pre-assumptions are made regarding the propagation pattern of the jammer. Experimental results showed that in less than two minutes and using only 3 smart-phones, our algorithm correctly detected a GNSS jammer within a 2 meters range in a Region-of-Interest (ROI) of 5000 m2.

Original languageAmerican English
Title of host publication2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
ISBN (Electronic)9781479959877
DOIs
StatePublished - 1 Jan 2014
Externally publishedYes
Event2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 - Eilat, Israel
Duration: 3 Dec 20145 Dec 2014

Publication series

Name2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014

Conference

Conference2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
Country/TerritoryIsrael
CityEilat
Period3/12/145/12/14

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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