## 1 Introduction  
Nowadays, Precise Point Positioning (PPP) is increasingly becoming widespread as an absolute positioning technique introducing a large variety of possible applications in both kinematic and static conditions. High-accuracy navigation and/or positioning can be performed worldwide in an absolute coordinate reference frame, and other PPP applications include the monitoring of areas subject to environmental risk, deformation controls of large structures (landslides, dams), plate tectonics studies [1, 2], the determination of Ground Control Point (GCP), resource management in remote areas, and sea-level measurement [3, 4, 5, 6]. Unlike the classical absolute positioning methods that use code measurements and the broadcast ephemeris to obtain the position of the receiver, PPP has the advantage of using the most precise carrier phase observables, and reducing the effect of all the types of errors and biases that affect GNSS (Global Navigation Satellite System) measurements. In this way, PPP is able to provide a precision level comparable to differential positioning without the support of ground stations. For this reason, PPP is particularly suitable for remote areas. GNSS technology is constantly changing, offering new opportunities to many applications in navigation, land surveying, and general geo-referencing. In particular, recent developments related to Europe's core constellation, Galileo, and China's own core constellation, the BeiDou navigation satellite system (BDS), have been underway and are fast oncoming completion. The introduction of these two advanced systems allows for the number of globally available GNSS satellites to be greatly grown, consequently also enhancing the robustness of GNSS as a whole. In the last two decades, the scientific community has paid particular attention to the multi-constellation approach in PPP techniques. Since 2009, the first real-time service providing GLONASS precise orbits and clocks was available [7; 8]. The use of multi-constellation double-frequency GNSS has demonstrated improved performance, in terms of precision and convergence time, with respect to single GNSS case [9; 10]. In [11], the authors proposed a multi-GNSS PPP model using data from the MGEX (Multi-GNSS Experiment) and BETN (BeiDou Experimental Tracking Network) ground tracking networks to fully take advantage of all available GNSS observables. The results showed that the integration of BeiDou, Galileo and GLONASS systems with GPS (Global Positioning System) significantly shortened the convergence time and improved the positioning accuracy. In particular, for the GPS-only solution, the positioning accuracy reached the decimeter level after a convergence time of thirty minutes, and the centimeter level after about 2 h for all three components of the position. GLONASS-only PPP configuration showed a slightly worse positioning accuracy and a longer convergence compared to GPS-only PPP. The BeiDou-only PPP provided good performance on the horizontal components, achieving few centimeter accuracies within one hour. Finally, the multi-GNSS (GPS/BeiDou/GLONASS/Galileo) PPP configuration presented the fastest convergence and highest accuracy for all three components. In 2015, the authors in [12] proposed a dual-frequency (DF) PPP model based on GPS and Galileo observables. The proposed model was based on a GPS/Galileo ionosphere-free (IF) linear combination PPP model, accounting for the additional combined biases, that are the Galileo satellite hardware delay and GPS to Galileo time offset (GGTO). These biases were lumped and considered as a new unknown parameter (noted as inter-system bias) into the PPP model. To obtain the best estimates for unknown parameters, a sequential least-squares estimation method was used. It is shown that, compared to the GPS-only configuration, 25% convergence time improvement and a sub-decimeter positioning accuracy level were achieved thanks to the developed PPP model.