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Session B1a: GNSS Integrity and Augmentation

Updates on GPS/Galileo Signal Quality Monitoring Making use of CUDA Processing and a High Number of Correlators
Mihai-Adrian Schipor, Florian Binder, Dominik Dötterböck, Institute of Space Technology and Space Applications, Universität der Bundeswehr München; Torben Schüler, Institute of Space Technology and Space Applications, Universität der Bundeswehr München & Geodetic Observatory Wettzell, Federal Agency of Cartography and Mapping (BKG); Thomas Pany, Institute of Space Technology and Space Applications, Universität der Bundeswehr München
Location: Beacon A
Alternate Number 1

This study presents an in-depth study on the integrity monitoring of Global Navigation Satellite System (GNSS) signals, emphasizing the essentiality of reliable signal transmission for autonomous systems. The program's methodology involves tracking GNSS satellites using advanced equipment, including the TWIN 2 and SFX1 radio telescopes and the Wettzell Laser Ranging System (WLRS). While focusing primarily on Galileo signals (E1BC, E5a, E5b), GPS signals (L1CA, L5IQ) are also considered. The signal quality monitoring tool's operational framework, outputs, and validation process forms the core of the study. It utilizes post-track analysis of satellite data, processed through MATLAB scripts and the MuSNAT [ 8 ] software receiver, for scrutinizing signal quality. A critical part of the study is the comparison between CUDA-based and CPU-based processing methods, with the former showing greater efficiency. Key metrics for signal quality analysis include the delta, double delta, threshold fluctuations, single sided ratio, and several other metrics. The research also explores various threat models for signal integrity, encompassing digital, analog, and mixed types. These models simulate different signal deformations that threaten GNSS-based systems. The validation of the SQM tool against these models is comprehensively detailed, showcasing its capability in detecting malicious signals and authenticating GNSS signals. In summary, the SQM tool stands out as an effective solution for GNSS signal integrity monitoring, with advanced capabilities in analyzing signal structure and performance. The paper suggests potential future expansions to include a broader range of GNSS signals and metrics, aiming to further elevate the tool's efficacy in signal quality monitoring.



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