Real-time global detection of wide-area interference events and their impact on PNT solutions

Kurzfassung

High integrity is a key requirement for safety-critical GNSS applications, such as autonomous car driving, maritime navigation, railway signaling and unmanned aerial vehicles (UAV). Over the last few years, particularly in view of the changing geopolitical situation, the requirement of high security has acquired a similar relevance for such applications due to the increasing number of artificial radio frequency interference (RFI) events occurred worldwide. In this context, signal monitoring systems play a fundamental role. In principle, monitoring can be used for various purposes: assessment of nominal system performance and service quality, failure detection in GNSS subsystems, for environmental analysis like natural RFI detection, multipath characterization as well as for the analysis of signal propagation effects due to the atmosphere. Of particular importance are monitoring systems that provide information that is globally-relevant or that is applicable for large geographical areas due to the number of users on which such information has impact. Nowadays, there are consolidated monitoring systems that have such characteristics, being used to serve specific safety-critical applications (e.g. aviation) such as the Wide Area Augmentation System (WAAS) and the European Geostationary Navigation and Overlay Service (EGNOS). These systems make use of specialized receivers to detect signal anomalies as well as to monitor and broadcast parameters and corrections, such as satellite ephemeris and clock errors and ionospheric delays in real time. The increasing need to consider high-security requirements for safety-critical applications calls for the implementation of new monitoring systems or the addition of extra layers to existing ones for the detection and analysis of events that hinder the continuity of navigation services. Of particular importance are events of natural or artificial RFI (also called jamming) given that they may threaten the uninterrupted use of navigation services, which is particularly hazardous for safety-of-life applications. In recent years, there have been efforts for the implementation of dedicated networks that are capable of detecting and locating jamming sources, primarily based on specialized receiver and antennas as well as networked architectures. Among the most prominent examples are the GNSS Interference Monitoring and Detection System (GIMAD), and the GNSS Interference Detection and Analysis System (GIDAS), both developed under the Navigation Innovation and Support Program (NAVISP) of the European Space Agency (ESA). In the case of GIMAD, the key element consists of portable stations that can be deployed to build interference detection and location networks of any scale. On the other hand, GIDAS’ concept is based on the installation of permanent and portable stations that are used to create a monitoring network in a zone or region of interest. Most jamming events occur and have major impact at the local level. In past studies, several efforts have been devoted to the detection, analysis and mitigation of these type of events. However, in recent years, sources of jamming that have an impact over much larger geographical areas have also been detected through their effect on Automatic Dependent Surveillance - Broadcast (ADS-B) signals from airplanes. Likewise, recent analyses have shown that jamming is not limited to sources located on or near the surface of the Earth, but it may also be originated in space, i.e. by a satellite. As this type of space-based jamming has an impact that may extend to a global scale (i.e. based on the orbit of the jamming source), the detection of such events is also of primary importance for a variety of safety-critical applications around the world, namely, not only for specific ones, like aviation. This contribution presents a strategy of a monitoring scheme for multi-frequency GNSS signals aiming at station-level anomalous event detection on a global scale. This scheme uses a unified monitoring approach to detect anomalous transient changes in signal power and code biases. Unlike many current systems, the proposed strategy does not require specialized receiver data, is not application-specific and its detection capabilities are not limited to a certain geographical area. Instead, it leverages observations from the publicly-available, continuously-operated and globally-distributed network of the International GNSS Service (IGS). For interference detection, given its capability of event detection on a global scale, the proposed strategy can work as a complementary strategy for existing systems (e.g. GIDAS or GIMAD) that are capable of performing a more in-depth analysis, like interference classification and jamming source location. In this way, the presented monitoring scheme aims at offering situational awareness for natural or artificial RFI events beyond the footprint of dedicated networks. The proposed scheme is based on the computation of simple metrics using time differences of carrier-to-noise density (C/N0) and dual-frequency geometry-free pseudorange observations for all satellites and stations under consideration. To provide a flexible support to a variety of current monitoring systems, the proposed metrics have been tailored to be implemented in real time (e.g. with observation data rates of 1 Hz). In a second step, for each station, robust M-estimators are employed to compute statistic and metric values for all signals under analysis. The resulting metrics are then analyzed to detect possible anomalous events. Finally, the results from various stations are ensembled to evaluate if a wide-area interference event has occurred. By analyzing also receiver code biases, the proposed strategy can provide more information about the level of impact of such events as well. To test the presented monitoring scheme, high-rate observation data from the IGS from 2025 were employed in this contribution. Aside from the analysis of known space-based transient jamming events occurred in this year, natural RFI events due to the solar activity were also investigated. Lastly, the impact of this kind of events on standard and precise GNSS positioning algorithms are presented.