Colloquium: Iván Sermanoukian Molina (Space)

Over the past decade, satellite navigation systems have advanced significantly, with GNSS becoming essential across numerous fields. This growth has driven the modernisation of systems like GPS and GLONASS and led to the creation of new ones, such as Galileo. The European Space Agency’s Navigation Support Office (NSO) leverages GNSS for precise applications and recently upgraded its processing system with the CHAMP (Consolidated High Accuracy Multi-GNSS Processing) framework, enabling efficient, constellation-wise data processing and solution comparisons. This thesis addresses multi-GNSS processing inconsistencies in the NSO, focusing on refining single-constellation solutions for reliable integration. A Python-based extension of CHAMP was developed, aiding GNSS large-scale data analysis, tracking anomalies, and addressing inconsistencies. Key findings include significant Length of Day inconsistencies in GPS and suggestions for enhancing non-gravitational models and empirical accelerations. Recommendations are made to improve NSO products by fine-tuning these models, achieving robust, cohesive multi-GNSS solutions.

Supervisor: Jose van den IJssel