Combined architecture for multi-dimensional signal quality enhancements in GNSS receivers

Multipath, interference and ionospheric distortions are three of the main error sources in satellite-based positioning. As Global Navigation Satellite Systems (GNSS) were designed to operate in perfect line-of-sight conditions, the GNSS observables are highly influenced by the signals arriving to the receiver along multiple propagation paths in locations with increased possibility of reflection or refraction of the signal, such as urban scenarios. Furthermore, due to their very low power at the Earth surface, GNSS signals are vulnerable to Radio Frequency Interference (RFI), which can severely degrade the receiver performance. Finally, ionosphere is another important error source in single frequency positioning.
Taking into account these three main error sources and some of the most promising detection and mitigation methods, we propose a combined architecture for future GNSS receivers including advanced multipath detection for integrity assessment, jamming interference detection, and a Data Driven (DD) framework for long term near real time ionospheric modeling.