Time Frequency and Statistical Inference Based Interference Detection Technique for GNSS Receivers

With the increasing use of global navigation satellite systems (GNSS) in myriad applications, ensuring the integrity of the GNSS signals has become of paramount importance. Radio frequency interference (RFI), either nonintentional or intentional (jamming), is a major concern for GNSS operators. We propose a time-frequency and statistical inference technique based approach for detecting various RFI types with varying bandwidths. The pseudo Wigner-Ville distribution is used to estimate the time-varying instantaneous frequency (IF) of the received GNSS signals and a known interference-free signal. A two-population F-Test is then applied to the two variances of the IF estimates to detect the presence of interference. We theoretically derive the parameters in the distribution function of the test statistic under the null hypothesis, which are then used to accurately determine the detection threshold for a given fixed significance level. Extensive simulations are performed to verify the effectiveness of the proposed method for detecting several types of interference. For a given sample size and significance level, the proposed approach improves the detection performance by up to 4 and 3 dB for narrowband and wideband interferences, respectively, without incurring additional computational complexity when compared with other approaches reported in the literature.