GNSS Spoofing Network Monitoring Based on Differential Pseudorange.

Area of Science:

• Navigation and Positioning Systems
• Signal Processing
• Cybersecurity

Background:

• Global Navigation Satellite System (GNSS) applications are increasingly vulnerable to spoofing attacks.
• Existing anti-spoofing solutions primarily focus on individual receiver-based detection during an attack.
• There is a need for proactive spoofing detection mechanisms that monitor an area.

Purpose of the Study:

• To propose and validate a novel spoofing network monitoring (SNM) mechanism for detecting GNSS spoofing within a geographical area.
• To develop an algorithm that leverages Time Difference of Arrival (TDOA) properties to distinguish between authentic and spoofed signals.
• To demonstrate the effectiveness of SNM in identifying spoofing even when the network is not actively under attack.

Main Methods:

• Implementation of a network comprising multiple receivers and a central processing unit.
• Measurement of TDOA using the differential pseudorange to carrier frequency ratio (DPF).
• Development of an algorithm to identify overlapping DPFs characteristic of spoofing signals, triggering an alarm when found within a narrow range.

Main Results:

• The proposed SNM methodology achieved a 99.99% detection probability in simulations and partial field trials.
• A low false alarm rate of 0.01% was recorded.
• The system effectively distinguished between dispersed authentic signal TDOAs and overlapping spoofing signal TDOAs.

Conclusions:

• The SNM mechanism offers a robust solution for detecting GNSS spoofing across an area, independent of active network attacks.
• SNM can provide timely alerts to users and enhance the reliability of GNSS performance monitoring systems like CORS and GAARDIAN.
• This approach significantly improves the security and integrity of critical GNSS-dependent applications.