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

Area of Science:

• Navigation Systems
• Signal Processing
• Cybersecurity

Background:

• Global Navigation Satellite Systems (GNSS) are critical for modern navigation, providing essential position and timing data.
• Increasing reliance on GNSS makes them vulnerable to jamming, posing significant threats to various applications.
• Jamming interference can disrupt navigation accuracy and availability, necessitating robust countermeasures.

Purpose of the Study:

• To develop a novel framework for detecting, tracking, and localizing Global Navigation Satellite Systems (GNSS) jammers.
• To address the growing problem of GNSS jamming and its severe ramifications in modern navigation.
• To enhance the resilience and reliability of navigation systems against malicious interference.

Main Methods:

• A Bayesian jamming detection algorithm is proposed to identify and track multiple jammers within a defined area.
• A jamming coverage map algorithm, analogous to cellular network maps, is introduced to identify weak GNSS reception zones.
• The dynamic nature of jamming is addressed by creating time-varying coverage maps to detect evolving interference patterns.

Main Results:

• The proposed framework successfully detected and tracked multiple jammers in simulations and field experiments.
• The jamming coverage map algorithm effectively identified areas with degraded GNSS signal reception.
• The combined algorithms enabled the accurate localization of arbitrary GNSS jammers within the region of interest.

Conclusions:

• The developed framework offers a viable solution for mitigating GNSS jamming threats.
• The ability to detect, track, and localize jammers significantly improves navigation system security.
• The proposed method enhances the robustness of navigation systems in the presence of jamming interference.