GNSS Spoofing Detection Based on Power Monitoring Combined with SQM

‍ ‍Spoofing interference seriously jeopardizes the safe operation of the Global Navigation Satellite System （GNSS）， which results in errors in various information about position， velocity and time. Signal quality monitoring （SQM） methods have a simple implementation process and a better detection performance， which has a better detection probability at the same false alarm probability. SQM methods have received extensive attention from scholars at home and abroad. Ratio metric is one of the classic Signal Quality Monitoring （SQM） methods， it realizes spoofing detection by detecting whether the correlation peak is distorted. Once the slope of the correlation peak increases or decreases abnormally， the output of the Ratio metric would be changed. Ratio metric is widely used in the field of spoofing detection. In order to detect spoofing， Power combined with Signal Quality Monitoring （PCS） metric we proposed in this paper is improved on the basis of the Ratio metric. By performing the sum and difference operation on the correlation output of the early channel， the prompt channel and the late channel for the tracking loops， the PCS metric can not only monitor the power abnormality of the received signal， but also detect whether the correlation peak is distorted， realizing signal power monitoring and signal quality monitoring of correlation output to the tracking loops at the same time. The output of the PCS metric can also eliminate the influence of the carrier phase error on the detection results. Using the fourth data of the Texas Spoofing Test Battery （TEXBAT） intermediate spoofing data set of the University of Texas to conduct a series of experimental analysis to evaluate performance of PCS metric on intermediate spoofing. The results show that， compared with the Ratio metric and power monitoring， the PCS metric combines the advantages of both， which has better detection performance， and higher detection probability at the same false alarm probability. Moreover， the output value of PCS metric at different moments can better reflect variation of the superposed signal power over time caused by spoofing signal， which in turn reflects the intermediate spoofing implementation process. According to the output value of the PCS at different moments， the PCS metric realizes detect spoofing earlier.