Recognition of GNSS Jamming Patterns in ADS-B Data

Abstract

With the increasing dependency on the Global Navigation Satellite System (GNSS) for navigation and surveillance, aviation is focusing on mitigation of threats caused by a possible system unavailability due to jamming or spoofing. This research deals with pattern recognition of the time evolution of quality indicators in transmitted Automatic Dependent Surveillance - Broadcast (ADS-B) messages during GNSS jamming in non jammed data over Central Europe. An evaluation of the quality indicators from all messages within a one month interval is presented. A practical jamming experiment was done to determine how the quality indicators are changing during a jamming presence. Afterwards, the results of the experiment are used as a foundation for the proposed jamming detection technique using ADS-B data based on pattern recognition and cluster analysis. A natural presence of a quality indicators variability is proven in the data using these methods, similar to the indicators variability during GNSS jamming.