Spoofing Detection and Mitigation in a Multi-correlator GPS Receiver Based on the Maximum Likelihood Principle.

Area of Science:

• Navigation Systems
• Signal Processing
• Cybersecurity

Background:

• Spoofing poses a significant threat to navigation systems, being difficult to detect and easily implemented with repeaters.
• Existing anti-spoofing methods primarily focus on detection, lacking effective counterfeit signal removal capabilities.

Purpose of the Study:

• To investigate the feasibility of applying multipath mitigation techniques for GPS anti-spoofing.
• To propose and validate a novel algorithm for detecting and removing spoofed signals.

Main Methods:

• Analysis of similarities between multipath interference and GPS spoofing.
• Development of a novel algorithm based on maximum likelihood (ML) estimation.
• Construction of tracking channels with multi-correlators for signal detection and removal.

Main Results:

• The proposed algorithm successfully detects and removes counterfeit GPS signals.
• Experimental validation using a software receiver and recorded intermediate frequency (IF) signals confirmed effectiveness.
• Ensured the receiver locks onto authentic signals even under spoofing conditions.

Conclusions:

• Multipath mitigation strategies are feasible for addressing GPS spoofing.
• The novel ML-based algorithm provides an effective solution for detecting and removing spoofed signals.
• The method enhances the robustness of navigation systems against sophisticated spoofing attacks.