Signal Quality Monitoring Aspects in GNSS Signals Affected by Evil Waveforms

Abstract

The objective of this paper is to study, analyze and evaluate the impact of Evil Waveform (EWF) distortions in GNSS receivers and assess the performance of a developed mechanism for EWF detection in both static and vehicular environments. Building on the lessons learned from previous semi-analytical (SA) test campaigns, and with the objective of proving the concept on real receivers, an in-phase and quadrature (IQ) EWF injector was developed to generate signals affected by EWF. The purpose is to perform an analysis of the impact of such distortions on a monitoring station and on-board receiver. To assess the signal quality monitoring (SQM) in the designed mechanism, the generated signals with EWF are processed with the GMV XRC software receiver, obtaining bit true correlator values time series, which are then analyzed by the SQM algorithm. The developed tests include both GPS and Galileo signals affected by EWF in static and vehicular dynamic scenarios, to have a broader range of results for analysis and also analyze the feasibility of EWF monitoring on on-board receivers. Real captured signals were also utilized to document the EWF detector’s behavior in its the most realistic application scenario possible. From the IQ tests, it was observed that the EWF detector’s performance targets (in terms of probabilities of missed detection and false alarm and in terms of time-to-alert) met in some occasions with poorer performances when considering dynamics in the user receiver. Furthermore, tests with a commercial off-the-shelf (COTS) receiver are carried out, processing GPS L1 C/A signals, aiming to analyze the impact the EWF phenomenon has on PVT estimates. It is observed that the u-blox receiver experiences a performance degradation in position estimates when subject to EWF. Taking the whole campaign of tests into account, i.e., the conjunction of results from SA, IQ and real signal simulations, it is concluded that the way forward in terms of EWF detection should be through the deployment of a network of static monitoring stations in detriment of on-board detection, as the former systematically outperforms the latter.