Save our roads from gnss jamming: A crowdsource framework for threat evaluation

Roi Yozevitch, Revital Marbel, Nir Flysher, Boaz Ben-Moshe

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish
Article number4840
Issue number14
StatePublished - 2 Jul 2021


  • Accurate orientation for autonomous robotics
  • Global orientation sensor


Dive into the research topics of 'Save our roads from gnss jamming: A crowdsource framework for threat evaluation'. Together they form a unique fingerprint.

Cite this