In this study, the NeQuick G and Klobuchar models are evaluated by monitoring performance issues related to ionosphere activity for single-frequency users. The effects of radio frequency (RF) signal propagation through the ionosphere may have a significant impact on satellite communication and navigation systems because of geomagnetic field geometry near the magnetic equator and in the proximity to the high- and low-latitude zones. An ongoing challenge is determining how accurate the ionospheric models employed by existing Global Navigation Satellite Systems (GNSSs) are. This work investigates the patterns of total electron content (TEC) fluctuations over distinct zones from 1 January 2019 to 30 June 2022. Measurements are collected at station networks deployed worldwide. Firstly, monthly and seasonal variations of TECs are analysed. Secondly, the TEC ’availability’ parameter, as the percentage of time when the TEC error is compliant with the specification of the Galileo Single-Frequency Ionosphere Algorithm (’NeQuick G’ model), is introduced. The TEC error defines the difference between (a) the model TEC, obtained by either the NeQuick G or the Klobuchar model over a given station, and (b) the reference TEC, based on observations from networks of GNSS receivers. Finally, the position, velocity, and time (PVT), along with broadcast group delays (BGDs) are analysed and the PVT accuracy is compared between the NeQuick G and Klobuchar models. In 3.5 years, the seasonal behaviour of TEC shows maxima during the March and October equinox and minima during the June and December solstice. Moreover, an increase in the TEC values and the amount of TEC errors are visible as we are approaching the next solar maximum. Preliminary results show a larger associated positioning error using the Klobuchar than the NeQuick G model. However, the difference is zone-dependent, most evident in equatorial regions. This collaborative study of the GRC, NMA, TUW, and SRC was performed under the Framework Partnership Agreements (GSA/GRANT/04/2016).

On 15 December 2016, the European Commission (EC) declared the provision of the Galileo Initial Services (IS). This marked a historical milestone in the Galileo program, towards the reaching of its Full Operational Capability. This allows users to navigate with performance-accuracy levels either matching or exceeding those obtained with other GNSS. Under the delegation of the EC, the European Union Agency for the Space Programme (EUSPA) has assumed the role of the Galileo Service Provider. As part of this service provision, the primary mission of the Galileo Reference Centre (GRC) is to provide the EUSPA and the EC with independent means for monitoring and evaluating the performance of the Galileo services, the quality of the signals in space, and the performance of other GNSS. This mission includes significant contributions from cooperating entities in the European Union (EU) Member States (MS), Norway and Switzerland. In particular, for a detailed assessment of the Galileo performance, these contributions include (but are not limited to) periodic dynamic campaigns in three different environments (aerial, terrestrial, and maritime). These campaigns were executed in the frame of the GRC-MS Project and use multi-constellation receivers to compare the navigation performance obtained with different GNSS. The objective of this paper is to present the numerical results obtained from these campaigns, together with several considerations about the experimental setup, the methodology for the estimation of the reference («actual») trajectory, and the reasons for possible performance degradations.

This paper describes a novel uplink scheduling (ULSC) algorithm for the Galileo system. The algorithm is designed to meet the stringent dissemination requirements that are currently foreseen for the provision of the Galileo Commercial Service (CS). In particular, these include “link availability” (LA) requirements that call for a minimum percentage of time (“availability”) when a minimum number of satellites (“space vehicles,” SVs), connected with an uplink station antenna, shall be in view with a generic user at a minimum elevation angle. LA requirements for CS were not fully considered in the design phase of the ULSC algorithm, which is currently implemented at the Mission and Uplink Control Facility (MUCF) of the Galileo Ground Segment. Similarly, this type of requirements is not considered in the ULSC algorithms available in the scientific literature. In particular, current solutions take into account only specifications about 1) the maximum “gap” duration between two subsequent contacts and 2) the minimum contact duration (MCD). In the new ULSC algorithm, LA specifications are effectively dealt with by a proper selection of the subset of the SVs to be allocated. In particular, the proposed selection scheme takes into account the specifications about both maximum gap duration and MCD while maximizing the “spatial diversity” of the solution. Such a diversity is defined as the union of the coverage areas of the allocated satellites. The performance of the new ULSC algorithm is evaluated based on the final deployment stage (full operational capability) of the Galileo system. The performance is also compared with that of the ULSC algorithm currently implemented at the Galileo MUCF (“reference” algorithm). Numerical results show that, compared to the reference algorithm, the average disconnection duration is reduced by more than 50%. In addition, the availability of the links needed for the provision of CS is significantly improved (up to 7%). As a result, preliminary LA requirements for CS are met using the new ULSC algorithm, while the reference algorithm has limitations to meet the new stringent LA requirements.

In this paper, we summarize the main outcomes of the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) parameters sensitivity and feasibility analysis of the algorithm described in the version 4.0 of the ADD [ADDv4.0], carried out within the European Union funded GESTA project. In particular, it analyses the impact on ARAIM user positioning algorithm performances, number of monitored fault modes, iterations and execution time when changing its input parameters or configuration. Besides, the paper proposes a series of steps, tests and verification procedures to validate an ARAIM algorithm implementation.