TY - JOUR
T1 - Save our roads from gnss jamming
T2 - A crowdsource framework for threat evaluation
AU - Yozevitch, Roi
AU - Marbel, Revital
AU - Flysher, Nir
AU - Ben-Moshe, Boaz
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/7/2
Y1 - 2021/7/2
N2 - 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 3G/4G 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.
AB - 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 3G/4G 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.
KW - Accurate orientation for autonomous robotics
KW - Global orientation sensor
UR - http://www.scopus.com/inward/record.url?scp=85110489980&partnerID=8YFLogxK
U2 - 10.3390/s21144840
DO - 10.3390/s21144840
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C2 - 34300580
AN - SCOPUS:85110489980
SN - 1424-8220
VL - 21
JO - Sensors
JF - Sensors
IS - 14
M1 - 4840
ER -