A Novel SQM Spoofing Detection Algorithm Based on IQ Channel Fusion

The Global Navigation Satellite System (GNSS) plays an irreplaceable strategic role in positioning, navigation, and timing (PNT) services. However, its open signal structure and inherent vulnerabilities make it highly susceptible to malicious spoofing attacks, posing serious threats to the security of critical infrastructure. To address the insufficient detection probability of traditional Signal Quality Monitoring (SQM) techniques - which rely solely on in-phase (I-channel) information - this paper proposes a novel SQM detection algorithm based on IQ channel fusion. The proposed method jointly analyzes the energy leakage characteristics of the quadrature (Q-channel) and signal distortion in the I-channel under spoofing interference to construct multidimensional detection metrics. Furthermore, a time-based moving average filter is introduced to suppress instantaneous fluctuations in the detection metrics, thereby enhancing the algorithm's robustness. Experimental results using real-world data from the TEXBAT dataset provided by the University of Texas at Austin's Radionavigation Laboratory demonstrate that the proposed algorithm achieves a 90.32% detection probability at a 10% false alarm rate - an improvement of 15 percentage points over the traditional Ratio algorithm. The method shows strong adaptability to low-power spoofing attacks in dynamic scenarios. Requiring no additional hardware, this approach offers a low-cost and highly reliable spoofing defense solution for single-antenna receivers, with broad application prospects in civilian navigation, military security, and autonomous driving.