The Galileo navigation satellite system is a global positioning European program designed to be completely interoperable with the analogues GPS and GLONASS positioning systems produced by the United States of America (USA) and the Russian Federation. With Galileo, the European Union aims at owning and providing an independent positioning/navigation service under civilian control [1
The Galileo program is constituted of two macro-phases: the In-Orbit Validation (IOV) phase and the Full Operational Capability (FOC) phase, which is to reach its conclusion in 2020. Specifically, the Galileo system robustness was tested during the IOV by means of two satellites (GIOVE-A and GIOVE-B) and, subsequently, with a reduced constellation of only four satellites (and the related ground infrastructure) with the aim to synchronize the satellites' onboard atomic clocks and to perform a precise orbit tracking. Further details related to the IOV phase can be found in the works of Simsky et al. and Steigenberger et al. [2
], while details related to the problems encountered during this phase can be found in [6
The first step toward the FOC phase was the European Commission’s formal announcement of the Galileo Initial Services (December 15, 2016). Once the FOC phase is concluded, the constellation will rely on 24 satellites (and two backup satellites for each orbital plane). In this phase, each satellite will take 14 h to complete its orbit at the altitude of 23,222 km [8
]. The whole system is designed to guarantee that at least four satellites are visible from each point on Earth. Indeed, 24 satellites will be equally distributed on three different orbital planes at 56° with respect to the equatorial plane [9
]. Further details related to the preliminary analysis of the FOC phase can be found in the novel work of Zaminpardaz S. and Teunissen P.J.G. [10
], while a detailed review of the project status (up to 5 July 2016) can be found in [11
The Galileo system is designed to provide different services. In this paper, the Galileo Open Service (OS) [8
] was considered. The Galileo OS is freely available for mass applications of synchronization and positioning. This service does not require any authorization and can be used by anyone equipped with an adequate receiver. The OS provides up to four carrier frequencies: E1 (1575.42 MHz), E5a (1176.45 MHz), E5b (1207.14 MHz), and E6 (1278.75 MHz). Over the past years, many authors have analyzed the outcomes of the Galileo mission in order to produce communications and scientific works. In particular, tests were produced before the IOV phase by using a simulated Galileo signal (e.g., [12
]). During the IOV phase, Odijk et al. [15
] proposed a paper describing the results of mixed GPS and GIOVE (Galileo In-Orbit Validation Element) A/B data. They placed emphasis on the equations related to the intersystem solution and found that the GPS and GIOVE data combinations were able to improve the instantaneous ambiguity resolution with regards to the single GPS data. Cai et al. [16
] analyzed the Galileo IOV positioning and signal performance by using the four IOV satellites. In their work, they considered the carrier-to-noise density ratio and multipath, and also analyzed the accuracy of the broadcasted ephemeris and IOV Galileo positioning performance. They concluded that the Galileo signal-to-noise ratio density was bigger than that of the GPS and that Galileo signals are characterized by smaller multipath and noise compared to GPS signals. Gaglione et al. [17
] proposed a study to demonstrate the improvement, of the Galileo constellation geometry, associated with the addition of two FOC satellites (FOC-FM1 and FOC-FM2). They also considered the pre- and post-orbital shifts of the FOC-FM1 satellite. Gioia et al. [18
] focused their work on the accuracy of the IOV measurements. One week of IOV acquisitions were processed to assess the results.
Studies characterized by GPS, GLONASS, BeiDou, Galileo, and QZSS comparisons are also reported in the literature. In particular, Tegedor et al. [19
] worked on precise orbit determination and precise point positioning (PPP) with GPS, GLONASS, Galileo, and BeiDou data. In their work, Galileo (IOV) and Beidu PPP were achieved after precise estimation of their orbit and clocks. This was possible thanks to the MGEX (IGS Multi-GNSS Experiment) data and to the data provided by a proprietary network (Fugro). Lou et al. [20
] used a multi-GNSS PPP model to evaluate the performance of the proposed model by using the MGEX data. Their analysis was validated with one month of acquisitions from the MGEX network. Multi-GNSS PPP was also the topic of the works proposed by Liu et al. [21
], Pan et al. [22
], and Afifi et al. [23
]. The work of Cai et al. [24
] aimed to assess and compare the multipath and receiver noises for GPS, BeiDou, GLONASS, and Galileo data by implementing the zero-baseline approach. Multi-GNSS performance evaluation was also the objective of the study proposed by Pan et al. [25
]. Their work focused on the contemporary use of four constellation data and on the implementation of different data combinations. MGEX data were also used in the paper of Guo et al. [26
]. In this case, the aim of the work was the assessment of the precise orbits and clocks for Galileo, BeiDou, and QZSS. This was performed by comparing the outcomes of different analysis centers and laser satellite ranging. Galileo data were involved also in real-time multi GNSS applications. Odijk et al. [27
] worked on real-time kinematic (RTK) based both on carrier-phase measurements and on pseudorange measurements acquired from the IOV Galileo satellites (already able to transmit navigation data). They tested different combinations considering only the Galileo signals and the combined Galileo and GPS signals and found that the Galileo and GPS combination could lead to an instantaneous ambiguity resolution. Odolinski et al. [28
] proposed a multi GNSS single-frequency real-time kinematic study, while Li et al. [29
] focused their attention on the real-time multi GNSS precise orbit determination, clock estimation, and positioning. Galileo data were also tested for attitude estimation (e.g., [30
]) and included in an online service devoted to the validation of multi-GNSS orbits by means of the satellite laser ranging [32
]. Lastly, Galileo data were measured for GNSS reflectometry polarimetric acquisitions over boreal forests [33
Thus far, this paper has shown the rigor with which, in many studies, the Galileo data were tested and assessed, especially in static sessions of measurements. However, to the authors’ knowledge, there are no examples of kinematic trajectory comparisons between the Galileo positioning performance and GPS- and GLONASS-derived trajectories, by using a reference trajectory derived from a precise Mobile Mapping System (MMS) as a benchmark. Specifically, in this paper, we propose a preliminary (and empiric) single-frequency kinematic performance assessment of Galileo, GPS, and GLONASS data acquired by using a Leica GS14 receiver, with reference to a trajectory estimated with MMS equipped with a POS/LV (Position and Orientation System for Land Vehicles), produced by the Applanix corporation. The Applanix system features a filtering system capable of integrating GNSS measurements with an IMU (inertial measurement unit) in order to guarantee a stable, reliable, and repeatable positioning solution for land-based vehicle applications [34
] and to ensure better positioning performance with regard to GNSS-only measurements (complementary and surpassing property [35
]). The performed trajectory comparisons were produced in such a way as to consider, for the three positioning systems, all the possible combinations (with four, five and six satellites for each considered constellation), by simulating a reduced operability for GPS and GLONASS. In this way, all the real and comparable working conditions, among the three different constellations, were simulated for a real case study. All the positioning solutions (and trajectories) were computed by means of the Free and Open-Source Software (FOSS) RTKLIB. RTKLIB is an open-source program package for standard and precise positioning and consists of a portable program library and several APs (application programs) already used in previous scientific communications [36
]. It supports: (1) standard and precise positioning algorithms with GPS, GLONASS, Galileo, QZSS, BeiDou, and SBAS; (2) single, DGPS/DGNSS, Kinematic, Static, Moving-Baseline, Fixed, PPP-Kinematic, PPP-Static, and PPP-Fixed positioning modes with GNSS for both real-time and post-processing (further details can be found in [41
The final results of the performed experiment were statistically assessed and showed a better Galileo planimetric performance while, from an altimetric point of view, the GPS and GLONASS systems performed better.
In this study, the comparison between Galileo, GPS, and GLONASS satellite positioning systems was proposed for a kinematic survey. The GNSS data were acquired with a Leica™ GS14 receiver and compared with the output obtained by a Mobile Mapping System (MMS), implementing integrated high-performance GPS/INS measurements. In particular, as far as the authors know, this is the first work that uses a precise MMS trajectory for the assessment of the kinematic performances of the Galileo system.
All the differential solutions were produced with the open-source set of libraries RTKLIB. Particularly, the RTKLIB CUI was used to simulate a reduced operational status for the GPS and GLONASS systems. Specifically, thanks to the RTKLIB CUI capabilities, it was possible, by using the Python programming language, to contemporarily execute many solutions. Indeed, the aim was to produce and compare, in sets of four, five, and six satellites, all the possible and real acquisition scenarios occurring during the survey.
In the authors' opinion, this experiment can be considered as a preliminary stress test for the Galileo system to verify if it has the potentiality to overpass the performances of the previous systems. Despite the effort to produce a fair comparison, the limited amount of Galileo satellites and their geometrical configuration (Figure 3
) put the Galileo system in a disadvantaged position with respect to the other two analyzed systems. This remains true even if the whole survey was planned to maximize the number of available Galileo satellites. Indeed, the displayed performance, especially from a planimetric point of view, cannot be justified only by the fact that the whole survey was organized to maximize the probability of Galileo acquisitions. This can also be understood by considering the filtering strategy adopted before the applications of Equation (6), and the results of the application of Equation (6), used to select the solutions that were compared. A first important result was represented by the presence of Galileo combinations able to pass the filtering process. This was necessary to build the next comparisons by applying the objective function. In fact, the aim of Equation (6) was to select only the best solutions (low deviations with respect to the MMS solution) and, among these, to choose the ones characterized by a high fix rate. Equation (6) was applied, without any other constraint, to the three analyzed constellations. However, the difference between Galileo and the other tested systems relied on the different number of possible combinations that, in some cases, was of two orders of magnitude (Table 3
For these reasons, the fact that the planimetric results are very encouraging should be considered, as stated by other researchers (e.g., [3
]), also in relation to the lower level of Galileo signal noise. From an altimetric point of view, the results were different. However, because of the lower level of statistical significance (not as clear as in the planimetric case) and the higher performance correlated to the increasing number of satellites shown in Table 4
, there is the need to analyze more data to properly assess the altimetric performances. In the authors’ opinion, the very small number of available combinations for the Galileo system and the non-uniform distribution in the visible satellite elevations were responsible for the lower altimetric performances.
Another result of this work is related to the experimental use of the software RTKLIB. The results performed for many combinations show a high occurrence of good solutions achieved with the “fix and hold” method for the GPS and GLONASS constellations. In case of post-processed analysis, this result can be instrumentally time-saving for those interested in using the RTKLIB set of tools. The same cannot be said for the Galileo constellation because of the lower amount of available satellites.
In this study, a big computational effort was produced to analyze 1 Hz multi-constellation kinematic data acquired during a one-hour field survey, planned to maximize Galileo satellites availability. The acquired data included a contemporary acquisition through an MMS equipped with a POS/LV produced by the Applanix corporation. The MMS acquisition was used as a reference trajectory, and the robustness of its solution was the most important hypothesis for the results shown in this study. This hypothesis can be considered always valid for research since it was found by coupling the GNSS technology with precise inertial instruments. Moreover, the MMS solution was calculated considering a higher amount of GNSS satellites when compared with the number of satellites used to perform the tests (four, five, and six). Lastly, only the L1, G1, and E1 frequencies were used in this experiment.
In order to present a real kinematic comparison between Galileo, GPS, and GLONASS satellite positioning systems, a reduced operational status was simulated for GPS and GLONASS. Moreover, it was possible to implement post-processed differential solutions with the Open-Source Software RTKLIB, thanks to the GNSS acquisitions of reference stations close to the surveyed areas.
The performed comparisons, whenever possible, were analyzed also by means of a statistical test. The outputs showed a clear and statistically significant planimetric performance of the Galileo positioning system, whereas the same result was not obtained from an altimetric point of view. However, in the authors’ opinion, this was especially due to the very small number of Galileo satellites and to their geometrical configurations.
Although these results were obtained with several computations, especially for the Galileo altimetric performance, they need to be reinforced by further experimental evidence. For this reason, they should be considered as preliminary results achieved by using a reference trajectory. Moreover, it is possible to conclude that the novel system is very promising also when used alone; in a disadvantaged comparison, it was able to produce better planimetric accuracy than the GPS and GLONASS positioning systems in a kinematic survey.
Future development of this work can include the kinematic inter-constellation comparison, the evaluation of the robustness of velocity and acceleration estimation with the Galileo constellation, and attitude estimations.