Abstract
The goal of this work is to study, analyze and evaluate the impact of Evil Waveform (EWF) distortions, stemmed from the aeronautical domain and the extension of detection strategies to automotive sector applications. The EWF event can be described as the transmission of a faulty PRN from a given GNSS satellite, being characterized/modelled by a combination of digital and analog distortions, which translates into different effects on the affected PRN, such distortions or Threat Models (TM) are described in the first part of the paper, illustrating its effects both at PRN and correlation level. The associated distortions imply specific Signal Quality Monitoring (SQM) mechanisms able to detect them. These techniques are described, clarifying its definition and proposing a new SQM solution from the joint processing of three types of tests in order to provide the desired robustness necessary for the detection of such events. This solution is theoretically studied via its probabilities of false alarm, missed detection and Time to First Alert and statistically proved through a Semi Analytical platform used in order to extract the previous values within the context of a more representative implementation, making use of proper tracking loops to generate time series of correlation values. Complementarily, with the objective of proving the concept on real receivers, an IQ EWF injector was developed to allow the generation of RF signals affected by EWF such that an analysis of the impact of such distortions on a monitoring station receiver can be performed. In order to assess the SQM mechanism designed, bit true correlator values time series are obtained from GMV XRC software receiver. An analysis on the performance of the implemented SQM mechanism finalizes the work presented in this paper, alongside an assessment on the potential use of this detector for the automotive sector, integrated within a network of integrity monitoring stations that provide information to correction services.
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