Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation

Global Navigation Satellite Systems (GNSS) jamming is an acute problem in the world of modern navigation. As more and more applications rely on GNSS for both position and timing, jamming ramifications are becoming more severe. In this paper we suggest a novel framework to cope with these threats. Fi...

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Main Authors: Roi Yozevitch, Revital Marbel, Nir Flysher, Boaz Ben-Moshe
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/14/4840
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spelling doaj-00110e41598f43b98358a55b1fa046572021-07-23T14:05:56ZengMDPI AGSensors1424-82202021-07-01214840484010.3390/s21144840Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat EvaluationRoi Yozevitch0Revital Marbel1Nir Flysher2Boaz Ben-Moshe3Department of Computer Science, Holon Institute of Technology, Holon 58102, IsraelDepartment of Computer Science, Ariel University, Ariel 40700, IsraelDepartment of Computer Science, Ariel University, Ariel 40700, IsraelDepartment of Computer Science, Ariel University, Ariel 40700, IsraelGlobal Navigation Satellite Systems (GNSS) jamming is an acute problem in the world of modern navigation. As more and more applications rely on GNSS for both position and timing, jamming ramifications are becoming more severe. In this paper we suggest a novel framework to cope with these threats. First, a Bayesian jamming detection algorithm is introduced. The algorithm can both detect and track several jammers in a pre-defined region of interest. Then, a jamming coverage map algorithm is offered. Similar to cellular <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mi>G</mi><mo>/</mo><mn>4</mn><mi>G</mi></mrow></semantics></math></inline-formula> coverage maps, such a map can detect “weak” GNSS reception spots and handle them. Since jamming interference can be a dynamic phenomenon (e.g., a vehicle equipped with a jammer), the coverage map changes with time. Thus, interference patterns can be detected more easily. Utilizing the offered algorithm, both on simulation and field experiments, we have succeeded to localize an arbitrary jammer(s) within the region of interest. Thus, the results validate the viability of the proposed method.https://www.mdpi.com/1424-8220/21/14/4840global orientation sensoraccurate orientation for autonomous robotics
collection DOAJ
language English
format Article
sources DOAJ
author Roi Yozevitch
Revital Marbel
Nir Flysher
Boaz Ben-Moshe
spellingShingle Roi Yozevitch
Revital Marbel
Nir Flysher
Boaz Ben-Moshe
Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation
Sensors
global orientation sensor
accurate orientation for autonomous robotics
author_facet Roi Yozevitch
Revital Marbel
Nir Flysher
Boaz Ben-Moshe
author_sort Roi Yozevitch
title Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation
title_short Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation
title_full Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation
title_fullStr Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation
title_full_unstemmed Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation
title_sort save our roads from gnss jamming: a crowdsource framework for threat evaluation
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2021-07-01
description Global Navigation Satellite Systems (GNSS) jamming is an acute problem in the world of modern navigation. As more and more applications rely on GNSS for both position and timing, jamming ramifications are becoming more severe. In this paper we suggest a novel framework to cope with these threats. First, a Bayesian jamming detection algorithm is introduced. The algorithm can both detect and track several jammers in a pre-defined region of interest. Then, a jamming coverage map algorithm is offered. Similar to cellular <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mi>G</mi><mo>/</mo><mn>4</mn><mi>G</mi></mrow></semantics></math></inline-formula> coverage maps, such a map can detect “weak” GNSS reception spots and handle them. Since jamming interference can be a dynamic phenomenon (e.g., a vehicle equipped with a jammer), the coverage map changes with time. Thus, interference patterns can be detected more easily. Utilizing the offered algorithm, both on simulation and field experiments, we have succeeded to localize an arbitrary jammer(s) within the region of interest. Thus, the results validate the viability of the proposed method.
topic global orientation sensor
accurate orientation for autonomous robotics
url https://www.mdpi.com/1424-8220/21/14/4840
work_keys_str_mv AT roiyozevitch saveourroadsfromgnssjammingacrowdsourceframeworkforthreatevaluation
AT revitalmarbel saveourroadsfromgnssjammingacrowdsourceframeworkforthreatevaluation
AT nirflysher saveourroadsfromgnssjammingacrowdsourceframeworkforthreatevaluation
AT boazbenmoshe saveourroadsfromgnssjammingacrowdsourceframeworkforthreatevaluation
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