Characterization and Early Awareness of Interference in GNSS L1/E1 Band using an Outlier Detection Algorithm

Abstract

One of the emerging challenges in the Global Navigation Satellite System (GNSS) is the vulnerability to radio frequency interference (RFI). The first step to deal with this problem is to identify and characterize the interference signals. In this work, we propose a combination of an outlier detection method and a time duration threshold checking to effectively detect and characterize RFIs in the GNSS L1/E1 band. The method is applied to the data recorded from a measurement campaign near the A9 highway in the southern part of Graz, Austria. During 6 hours of recording, three moving interference sources are identified and their average speeds, directions, and time-frequency characteristics are reported.