Robust Spoofing Detection for GNSS Instrumentation Using Q-Channel Signal Quality Monitoring Metric
Chao Sun, Joon Wayn Cheong, Andrew G. Dempster, Hongbo Zhao, Lu Bai, Wenquan Feng
Abstract
Signal quality monitoring (SQM) has been proven to be a simple and effective means for the detection of spoofing attacks for global navigation satellite system (GNSS) instruments. Some prevalent SQM metrics include Ratio and Delta metrics. However, such SQM metrics have inherent defects, such as limited spoofing detection accuracy and low robustness due to the false alarms caused by environmental effects, such as multipath. The construction of conventional SQM metrics is mainly based on the in-phase correlator outputs in the tracking loop of a GNSS instrument. It is known that the interaction between spoofing and authentic signals will cause leakage of correlation energy to the quadrature channel. This article proposes a new SQM metric using this abnormal quadrature channel energy as the primary indicator. A spoofing and multipath discrimination scheme based on intersatellite cross-check is further developed. The detection performance of the quadrature channel-based SQM metric is verified in spoofing and multipath scenarios using the well-known Texas Spoofing Test Battery (TEXBAT) dataset and real multipath data collected in Beihang University, respectively. Results demonstrate that the proposed method achieves a higher than 95% detection rate for the TEXBAT Scenario 2 with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$P_{\text {fa}}$ </tex-math></inline-formula> of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−2</sup> and an averaging time of 4 s, showing better detection sensitivity and robustness compared with conventional I-channel SQM metrics.