## 5 Conclusions  
Ambiguity resolution proved to be an important tool to level-up PPP towards instantaneous centimetre positioning. With all the frequencies being broadcast from all the major constellations in orbit, ambiguity resolution can be made to be more successful, especially during initial epochs of processing, bringing the PPP convergence time down. In this manuscript, a flexible multi-GNSS triple-frequency uncombined Decoupled Clock Model is introduced. Given that all satellites do not broadcast on three frequencies, as some only support two frequencies, the DCM was altered to be able to process and fix both dual-frequency and triple-frequency satellites simultaneously. This simultaneous processing requires careful handling of the PPP states and of the reference satellite, as the latter has to contain as many frequencies as the maximum number of frequencies being available in all satellites. The algorithm was first tested on static ICS data processed in kinematic mode, which showed that convergence below a decimetre for the horizontal component is possible within 2 min of processing at the 1-sigma (67 th percentile). After convergence, the horizontal rms reaches 1 cm, while the vertical rms reaches 2 cm. The third frequency is found to have a limited impact on the float solution, as most of its benefits are in the form of more successful ambiguity fixing during convergence, allowing for centimetre accuracies to be achieved faster; though the effect of both ambiguity resolution and the third frequency is relatively limited when it comes to the vertical component. The algorithm was also tested on kinematic data collected by driving a car in two different scenarios. The results show that quasi-instantaneous centimetre positioning is possible even with a moving receiver, as one dataset reached and stayed at 1 cm horizontal error for the whole duration of the dataset, while the other dataset managed to do so after 51 s. Though it was noticed that the environment can still have an impact on the level of noise in the position estimates, in high-multipath areas, for example. The work in this manuscript is novel in the fact that, rather than discarding satellites broadcasting only on two frequencies as is typically done, those satellites are included in the processing, alongside triple-frequency satellites. Doing so allows for improvements in the geometry, but also more reliable fixing of ambiguities. Having this flexible processing is shown to provide significant improvements compared to a dual-frequency-only or a triple frequency-only solution. The importance of this work is confirmed by the results, as they show that global instantaneous centimetre-level positioning is possible, even with vehicle data. Indeed, these results are based on ultra-rapid products generated from a global network, without the use of any local information. These results open the door for PPP to be used in real-time applications that require precise positioning, such as autonomous driving. The results are expected to further improve by adding additional frequencies, such as Galileo's E6 signal, or with the addition of BeiDou-3, which are all intended as future work. By doing so, it is expected that the results would improve even further, with more datasets being able to converge instantaneously. When it comes to kinematic datasets, the results can be further improved through careful handling of the multipath errors in areas where it would affect the positioning accuracy. Conceptualization, N.N. and S.B. ; methodology, N.N. ; software, N.N. ; investigation, N.N. ; writing--original draft preparation, N.N. ; writing--review and editing, N.N. and S.B. ; visualization, N.N. ; supervision, S.B. funding acquisition, S.B. All authors have read and agreed to the published version of the manuscript. This article/publication is part of the project GISCAD-OV that received funding from the European GNSS Agency under the European Union's Horizon 2020 research and innovation program under grant agreement No. 870231.