Automatic Classification of RFI Events From a Multi-Band Multi-site GNSS Monitoring Network

Anja Diez, Aiden Morrison, Nadezda Sokolova

Peer Reviewed

Abstract:	Global Navigation Satellite System (GNSS) data that is disturbed by jammer events is collected by the Advanced Radio Frequency Interference (RFI) Detection Analysis and Alerting System (ARFIDAAS). In this paper we present an automatic classification algorithm to categorize the observed jammer events into thirteen different jammer signal classes. The classification algorithm is based on functions and properties derived from the spectrogram of the data. The algorithm performance has first been validated using simulated/synthetic events. The information saved from the classification algorithm can be used to derive long term statistics on the occurrence of jammer signal types.
Published in:	Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022) September 19 - 23, 2022 Hyatt Regency Denver Denver, Colorado
Pages:	3907 - 3914
Cite this article:	Diez, Anja, Morrison, Aiden, Sokolova, Nadezda, "Automatic Classification of RFI Events From a Multi-Band Multi-site GNSS Monitoring Network," Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022), Denver, Colorado, September 2022, pp. 3907-3914. https://doi.org/10.33012/2022.18572
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