Galileo High Accuracy Service (HAS) Performance Analysis Report

Custom Icon   Introduction

Precise Point Positioning (PPP) technology can achieve high-precision positioning anywhere in the world. Compared with real-time dynamic differential positioning technology, PPP technology does not require a dense reference station network, but its accuracy relies on high-precision satellite orbits and clock deviation products. The Galileo satellite navigation system is a global navigation satellite system (GNSS) jointly developed by the European Union (EU) and the European Space Agency (ESA). Among them, the High Accuracy Service (HAS) issued by the Galileo satellite navigation system can provide real-time precision single point positioning (PPP) services worldwide. Since the birth of the Galileo satellite navigation system, many domestic and foreign scholars and experts have conducted a large amount of research on satellite signal modes, satellite data quality, navigation algorithms, positioning performance evaluation and other aspects based on simulated data or measured data.
Compared with RTK technology, PPP technology is a high-precision positioning mode based on state space domain correction. From the perspective of technological development, it integrates standard single-point positioning technology and wide area differential technology, and can achieve centimeter-level positioning accuracy within a global reference framework. Compared with RTK technology, PPP has the advantages of only requiring a single receiver, no need to set up a reference station, unlimited operating distance and low cost. Therefore, it has promising applications in maintaining and refining regional coordinate frameworks, precise timing, earthquake monitoring, ionospheric monitoring, and has gradually become one of the hot research directions in the field of satellite navigation. Fig.1 shows the comparison between single-point positioning and RTK positioning results using PPP-HAS. It can be seen that PPP positioning accuracy can achieve decimeter-level accuracy. In places not covered by the RTK CORS network, PPP can be used as a high-precision positioning to meet the positioning needs of general users.

Fig.1 Comparison of PPP-HAS positioning and RTK positioning results of Belgium site

This report focuses on the precision of the correction information provided by HAS, and uses SinoGNSS self-developed PPP-HAS program to evaluate the positioning performance of domestic and foreign measured data.
Fig.2 Working principle of PPP-HAS

Custom Icon   1 Data and method

1.1 Data sources and processing

    This report utilizes self-developed receivers from SinoGNSS for data collection. The data collection environment mainly in open sky. The tests was done over the globe, select some typical countries to analyse the performance in different location. It includes fours sites in China, and one site in Africa, South America, North America and Europe respectively. Multiple-station data undergoes continuous multi-day PPP testing for evaluation.


Fig.3 Test environment


The observation data used to evaluate the HAS service performance of the Galileo satellite navigation system come from data from 4 cities in China and 4 overseas countries. The specific site name distribution and the time of the samples displayed in the article are shown in Table 1.

Table1 Data distribution and sampling time
Sampling Location Latitude Longitude Data Sampling Statistics Date Report Image Display Date
China-Shanghai (Asia) 31.35°N 121.29°E 2023/09/01 - 2023/10/08 09/28 10:30-21:20 (static) 09/18, 09/22 (dynamic)
China-Beijing (Asia) 39.98°N 116.41°E 2023/10/17 - 2023/11/05 11/06 01:00-24:00
China-Guangzhou (Asia) 23.18°N 112.42°E 2023/12/02 - 2023/12/04 12/04 00:00-15:20
China-Xinjiang (Asia) 44.57°N 86.62°E 2023/10/17 - 2023/10/26 10/23 01:00-22:30
Uganda (Africa) 0.4150°N 32.59°E 2023/03/22 - 2023/03/26 03/22 16:30-00:00
Brazil (South America) 25.49°S 49.22°W 2023/03/27 03/27 12:00-20:00
Belgium (Europe) 50.35°N 4.892°E 2023/03/16 03/16 19:30-03/17 10:00
Canada (North-America) 53.60°N 113.92°W 2023/12/13 12/13 00:00-04:00


Table 2 shows the processing methods of ambiguity, clock bias and other related parameters in the positioning process.

Table 2 Solution Strategy
Main Parameters Solution Strategy
Observations Ionosphere-free combined pseudo-range and carrier wave observations
Sampling Rate 1Hz
Phase wrapping Model correction
Solid earth tide, ocean tide Model correction
Parameter estimation method Robust Kalman Filter
Ionospheric delay Ionospheric-free combined elimination
Ambiguity Parameter Estimation
Tropospheric delay Parameter Estimation
Satellite clock bias, orbit Using Galileo HAS products
Cycle slip detection Melbourne-Wübbena combination and geometric distance-free combination


1.2 Position methods

When using PPP-HAS for positioning, the basic observation equation of pseudorange and carrier wave is:


\( P_i = \rho_i + I_i + T + cdt_{r} - cdt^s - c(B_{r} + B^s) + \epsilon_{P} \)  (Eq.1)

\( \Phi_i = \rho_i - I_i + T + cdt_{r} - cdt^s - c(b_{r} + b^s) + \lambda_i N_i + \epsilon_{\Phi} \)  (Eq.2)


P represents the pseudo-range observation value, Φ represents the carrier observation value, λ represents the carrier phase wavelength, i represents that the error is related to the frequency of the signal, ρ represents the geometric distance between the satellite and the receiver, dtr and dts are the receiver clock bias and satellite clock bias respectively, I represents the ionospheric delay, T represents the tropospheric delay, Br, and Bs respectively represent the receiver-side hardware delay and satellite-side hardware delay of the pseudo-range part, br and bs respectively represent the receiver-side hardware delay and satellite-side hardware of the carrier part, N is the integer ambiguity of the carrier phase signal in cycles, ξ represents observation noise and other errors not modeled. When performing PPP positioning, establish an ionosphere-free combined model according to Eq. 3 and Eq. 4.


\( P_{IF} = \frac{f_1^2 P_1 - f_2^2 P_2}{f_1^2 - f_2^2} = \rho + cdt_{r} - cdt^{s} + T + \epsilon_{P_{IF}} \)  (Eq.3)

\( \Phi_{IF} = \frac{f_1^2 \Phi_1 - f_2^2 \Phi_2}{f_1^2 - f_2^2} = \rho + cdt_{r} - cdt^{s} + T + \lambda_{IF} N_{IF} + \epsilon_{\Phi_{IF}} \)  (Eq.4)


Eq. 3 and Eq. 4 are the ionospheric-free combined observation equations. The ionospheric-free combined combination model can eliminate the influence of the first-order ionosphere. The parameters to be estimated only include 3 position parameters, receiver clock bias, zenith tropospheric delay and combined carrier phase ambiguity.  After establishing the model, domestic and foreign base stations are selected to receive satellite observation data and HAS data, and the relevant parameters are processed according to Table2. Fig.4 is used to verify the ionosphere-free precise positioning.


Fig.4 Precision single point positioning algorithm process based on PPP-HAS service



Custom Icon   2 Performance analysis on static scene

2.1 PPP-HAS performance in China

This section mainly uses PPP-HAS to evaluate positioning accuracy. Fig.5-Fig.12 show the PPP positioning deviations in four different cities, where the horizontal axis is GPS time. From the figure, we can see the positioning results of the site after the results converge. The domestic positioning results are statistically calculated and averaged to obtain the final result.


When the horizontal accuracy of the positioning results is within 20cm and the accuracy for 100 consecutive epochs does not exceed 20cm, the results are considered to have converged. Table 3 provides average statistics of the positioning results of four domestic sites.

Table 3 Precision and convergence statistics of domestic sites
Sites E-S/cm N-W/cm U-D/cm Horizontal 2D RMS/cm (95%) Height 2D RMS/cm (95%) Convergence Time /min
Shanghai 8.7 6.1 17.9 19.7 26.9 23.8
Beijing 8.2 4.9 18.3 29.8 20.4 27.8
Xinjiang 9.2 8.9 16.3 21.4 33.0 27.4
Guangzhou 7.6 5.1 14.1 11.6 18.2 29.6
Mean Value 8.4 6.3 16.7 20.6 24.6 24.7


By following you can get detail information on each station for the accuracy.


Custom Icon   Site 1:  Shanghai


Fig.5 PPP-HAS positioning solution of Shanghai site


Fig.6 Plane positioning map of Shanghai site


Custom Icon   Site 2:  Beijing


Fig.7 PPP-HAS positioning solution of Beijing site


Fig.8 Plane positioning map of Beijing site


Custom Icon   Site 3:  Xinjiang province


Fig.9 PPP-HAS positioning solution of Xinjiang site


Fig.10 Plane positioning map of Xinjiang site


Custom Icon   Site 4:  Guangzhou province


Fig.11 PPP-HAS positioning solution of Guangzhou site


Fig.12 Plane positioning map of Guangzhou site

2.2 PPP-HAS performance in Worldwide

Except for testing in China, we selected some typical countries to conduct the performance testing. Fig.13-Fig.20 show the positioning deviations of each site. Table 4 statistics the multi-day accuracy average and convergence time of the selected sites.

Table 4 Statistics on accuracy and convergence of overseas stations
Sites E-S/cm N-W/cm U-D/cm Horizontal 2D RMS/cm (95%) Height 2D RMS/cm (95%) Convergence Time /min
Uganda 5.2 4.9 11.3 17.5 25.8 17.6
Brazil 6.3 3.0 12.1 24.0 25.1 13.8
Belgium 4.5 6.6 13.3 10.4 17.0 16.4
Canada 7.3 7.9 8.5 26.8 15.7 15.7
Mean value 5.83 5.6 11.3 19.67 20.9 15.87


By following you can get detail information on each station for the accuracy.


Custom Icon   Site 1:  Uganda in Africa


Fig.13 PPP-HAS positioning solution of Uganda site


Fig.14 Plane positioning map of Uganda site


Custom Icon   Site 2:  Brazil in South America


Fig.15 PPP-HAS positioning solution of Brazil site


Fig.16 Plane positioning map of Brazil site


Custom Icon   Site 3:  Belgium in Europe


Fig.17 PPP-HAS positioning solution of Belgium site


Fig.18 Plane positioning map of Belgium site


Custom Icon   Site 4:  Canada in North America


Fig.19 PPP-HAS positioning solution of Canada site


Fig.20 Plane positioning map of Canada site




Custom Icon   3 Performance analysis on dynamic scene

In order to examine the performance of real-time dynamic precision single-point positioning based on the PPP-HAS service, a vehicle dynamic test experiment was conducted from September 01 to October 10, 2023. The module used was SinoGNSS K803 board, and the environment was an open environment. Fig.23 shows the test results in Shanghai on November 7, Fig.26 shows the test results in Brazil on December 4. Compared with the high-precision RTK results, it can be seen that the difference between the positioning results of real-time dynamic PPP-HAS after stability and the positioning results of high-precision RTK is in decimeter level.


Fig.21 PPP-HAS real-time dynamic positioning results-1


Fig.22 Difference between PPP-HAS and RTK results-1


Fig.23 PPP-HAS real-time dynamic positioning results-2


Fig.24 Difference between PPP-HAS and RTK-2



Custom Icon   Conclusion

The Galileo PPP HAS service covers the vast majority of countries worldwide, with an average convergence time of 15 to 20 minutes and an average accuracy of 20cm 2D RMS after convergence. European countries tend to experience better performance compared to others.


The Galileo High Accuracy Service (HAS), a free satellite-based Precise Point Positioning (PPP) solution, delivers unparalleled benefits across a myriad of applications. From traditional surveying and GIS data collection to dynamic environments such as precision agriculture, UAV, and intelligent driving, Galileo HAS revolutionizes global positioning with its precision and reliability.




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