Achieving high-accuracy and robust navigation solutions is crucial in various domains, such as autonomous vehicles, aviation, and mobile devices. In this context, Global Navigation Satellite Systems (GNSS) play a pivotal role in modern navigation and positioning applications due to their capability of providing absolute position fixes. However, many target applications have strict safety and precision requirements, which standalone GNSS is unable to achieve in harsh environments such as urban scenarios, thus requiring improvements in terms of accuracy and robustness. Factor graphs have proven to be a powerful mathematical framework for modelling and solving complex estimation and optimization problems such as Simultaneous Localization and Mapping (SLAM).