A new approach for GNSS spoofing detection using power and signal quality monitoring

Global navigation satellite system signals are highly susceptible to spoofing attacks. Signal quality monitoring (SQM) methods are simple and easy to detect spoofing. However, traditional SQM methods are only effective for matched-power cases and exhibit high detection probability only for a short time. This study introduces a new approach, exploiting anomalies in receiver correlation outputs during spoofing. It efficiently detects signal amplitude fluctuations and correlation peak distortions. The Texas Spoofing Test Battery dataset and the real BeiDou spoofing data are used to evaluate the detection performance of the proposed approach. The results show that the proposed approach has excellent detection performance in various spoofing cases, including matched-power, overpowered, static, and dynamic cases. This approach surpasses traditional SQM metrics in detection probability and sensitivity to spoofing stages. Importantly, the proposed approach detects spoofing early.