Generalized Likelihood Ratio Satellite Navigation Spoofing Detection Algorithm Based on Moving Variance

The vulnerability of Global Navigation Satellite Systems (GNSS) to spoofing limits their widespread use in military security and national economy. Therefore, fast and accurate detection of GNSS spoofing is of great significance. When spoofing cannot be accurately detected in the capture tracking phase, spoofing detection needs to be performed again at the localization solver. In order to detect the spoofing jamming of Global Navigation Satellite System in pseudo-range measurements, a generalized likelihood ratio satellite navigation spoofing detection algorithm based on moving variance is proposed by analyzing the pseudo-ranges cleared by the positioning of global satellite navigation signals. A new data subset is created by calculating the variance of the pseudo-range of different satellites at the same time and moving it forward. The variance is calculated again by this data subset to obtain the moving variance, the generalized likelihood ratio detection model is used to calculate the detection statistics of the pseudo-range movement variance, the detection statistic is then compared to the detection threshold under the condition that the probability of false alarm is $1\times 10 ^{-7}$ , so as to realize the spoofing jamming detection of global satellite navigation receiver for pseudo-range. Taking the software receiver as the experimental platform, the effectiveness of the proposed algorithm is verified by comparing it with two other algorithms. The result show that when the number of spoofed satellites is less than 9, the algorithm has a good detection effect. When the false alarm rate is $1\times 10 ^{-7}$ , the average prediction accuracy rate is kept above 98 %.