Moving variance-based signal quality monitoring method for spoofing detection

Abstract

Signal quality monitoring (SQM) techniques, originally designed for multipath detection, were recently found to be useful to identify underway spoofing attacks. Conventional SQM-based methods directly employ the values of the SQM metrics to monitor spoofing attacks. They have good feasibility with simple structures but suffer from significant performance loss for frequency unlocked spoofing cases due to the drift of the relative carrier phase. We developed an enhanced SQM technique for detecting an onset of spoofing. It is known that the value of the SQM metric fluctuates significantly during the interaction stage between the counterfeit signal and authentic signal. As the variance of metric can better reflect this fluctuation, we choose the moving variance (MV) of the SQM metric as a new metric to detect the occurrence of spoofing. The basic principle of the proposed method is introduced. Its ability to detect spoofing has been validated using the Texas Spoofing Test Battery dataset and compared with the classic SQM methods and a moving average-based method. The results show that the proposed MV-based SQM method is advantageous in the detection of an onset of a frequency unlocked spoofing attack.