A Robust Reliability-Centric Method for Swift Spoofing Signal Detection in Advanced GNSS Security

Global navigation satellite systems (GNSSs) have been proven to be susceptible to spoofing signals, presenting a significant threat to the security and stability of nations and societies. Signal quality monitoring (SQM) can be utilized to identify spoofing attacks on GNSS signals. However, traditional SQM metrics exhibit inadequate responsiveness and resolution in detecting spoofing signals, and further the multi-correlator technology based on the traditional SQM metrics needs too high computation cost and still ignores abnormal power problem in the spoofing process. To address these issues, this paper proposed a novel spoofing detection method based on reliability theory for assessing the reliability of GNSS signals. A third-order central moment of GNSS signal correlation peak outputs is selected as the characteristic state equation, and then the reliability metric of GNSS signals is calculated by using the mathematical expectations and standard deviations of the characteristic state equation so as to determine the degree of distortion. After the intermediate spoofing interference dataset of Texas Spoofing Test Battery (TEXBAT) is analyzed experimentally, the proposed reliability metric is demonstrated to detect the presence of spoofing interference more rapidly, thereby mitigating irreversible harm. Additionally, it exhibits superior detection performance, real-time capabilities, and enhanced robustness in terms of identifying spoofing attack.