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...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/14/4840 |
id |
doaj-00110e41598f43b98358a55b1fa04657 |
---|---|
record_format |
Article |
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 |
_version_ |
1721285938025332736 |