# Analyses of GLONASS and GPS+GLONASS Precise Positioning Performance in Different Latitude Regions

^{1}

^{2}

^{3}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Evaluation Methods

#### 2.1. Data Quality Check

- Data Integrity (DI). Data integrity rate is the recorded valid observation data divided by the receivable observation data calculated by ephemeris and the station location.
- Signal-to-Noise Ratio (SNR). SNR is the ratio of signal power to noise power within a given bandwidth. It is usually expressed in the unit of decibels.
- Pseudorange Multipath (MP). Pseudorange multipath indicators are computed using the linear combination of pseudorange and carrier phase observations:

#### 2.2. Constellation Visibility Analysis

- The number of visible satellites. The mean number of visible satellites in each network at each epoch is computed, and the observed probability of different positioning combinations is also analyzed.
- The elevation angle of visible satellites. The mean elevation angle of visible satellites in each network at each epoch is computed, and the occurrence probability corresponding to different degrees is evaluated.
- The Position Dilution of Precision (PDOP). The mean PDOP of each network at each epoch is calculated.

#### 2.3. DD Network Processing Strategy

#### 2.4. Static PPP Processing Strategy

#### 2.5. Accuracy Assessment

## 3. Data Selection

- To comprehensively evaluate and compare the performance of GLONASS stand-alone mode, GPS stand-alone mode, and GPS+GLONASS combined mode, the station’s receiver should receive both GPS and GLONASS observations. The receivers employed in the three networks are listed in Table 2, Table 3 and Table 4, respectively.
- Using the GPS antenna PCC model for GLONASS will introduce systematic bias [9,27,28]. To avoid this bias, the station’s antenna and radome types should have GPS and GLONASS-specific PCC models in the IGS antenna files. The antenna and radome types used in the three networks are also given in Table 2, Table 3 and Table 4, respectively.
- The baseline accuracies are related to the length of the baseline [29]. To precisely assess the performance of GLONASS in terms of DD network processing, the mean baseline lengths of the networks should be similar.

## 4. Results and Discussion

#### 4.1. Data Quality

#### 4.2. Constellation Visibility

#### 4.3. DD Network Solutions

#### 4.3.1. Accuracy of Coordinates

#### 4.3.2. Ambiguity Fixing Rate

#### 4.3.3. Tropospheric Estimates

#### 4.4. Static PPP Results

#### 4.4.1. Positioning Accuracy

#### 4.4.2. Convergence Time

#### 4.4.3. Tropospheric Estimates

## 5. Conclusions

- The data integrity rate of GLONASS is lower than that of GPS;
- Both GPS and GLONASS have the mean maximum number of visible satellites in high latitudes; however, the mean elevation angle of GLONASS is higher than that of GPS;
- GLONASS has a comparable or even better positioning accuracy than GPS in high latitude regions, and the coordinates of GPS+GLONASS show the best accuracy;
- GPS stand-alone mode gets the best positioning accuracy in middle latitude regions, and the additional GLONASS observations show no positive impact on GPS+GLONASS processing;
- GLONASS shows the worst accuracy in low latitude regions, but the adding of GLONASS can improve the positioning accuracy of GPS+GLONASS processing mode when compared to GPS-only processing mode;
- The addition of GLONASS will reduce the convergence time and improve the accuracy of ZTDs for PPP processing in high, medium, and low latitude regions.

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

- Hein, G.W. Status, perspectives and trends of satellite navigation. Satell. Navig.
**2020**, 1, 22. [Google Scholar] [CrossRef] [PubMed] - Dodson, A.H.; Moore, T.; Baker, F.D.; Swann, J.W. Hybrid GPS+GLONASS. GPS Solut.
**1999**, 3, 32–41. [Google Scholar] [CrossRef] - Stewart, M.P.; Tsakiri, M.; Wang, J.; Monico, J.F. The contribution of GLONASS measurements to regional and continental scale geodetic monitoring regimes. Earth Planets Space
**2000**, 52, 877–880. [Google Scholar] [CrossRef] - Bruyninx, C. Comparing GPS-only with GPS + GLONASS positioning in a regional permanent GNSS network. GPS Solut.
**2007**, 11, 97–106. [Google Scholar] [CrossRef] - Habrich, H. Evaluation of analysis options for GLONASS observations in regional GNSS networks. In Geodetic Reference Frames; Springer: Berlin/Heidelberg, Germany, 2009; pp. 121–129. [Google Scholar]
- Cai, C.; Gao, Y. Precise point positioning using combined GPS and GLONASS observations. Positioning
**2007**, 6, 13–22. [Google Scholar] [CrossRef] - Alcay, S.; Inal, C.; Yigit, C.; Yetkin, M. Comparing GLONASS-only with GPS-only and hybrid positioning in various length of baselines. Acta Geod. Geophys. Hung.
**2012**, 47, 1–12. [Google Scholar] [CrossRef] - Nardo, A.; Huisman, L.; Teunissen, P.J.G. GPS+GLONASS CORS Processing: The Asian-Pacific APREF Case//Earth on the Edge: Science for a Sustainable Planet; Springer: Berlin/Heidelberg, Germany, 2014; pp. 239–246. [Google Scholar]
- Zheng, Y.; Nie, G.; Fang, R.; Yin, Q.; Yi, W.; Liu, J. Investigation of GLONASS performance in differential positioning. Earth Sci. Inform.
**2012**, 5, 189–199. [Google Scholar] [CrossRef] - Cai, C.; Gao, Y. Modeling and assessment of combined GPS/GLONASS precise point positioning. GPS Solut.
**2013**, 17, 223–236. [Google Scholar] [CrossRef] - Yigit, C.O.; Gikas, V.; Alcay, S.; Ceylan, A. Performance evaluation of short to long term GPS, GLONASS and GPS/GLONASS post-processed PPP. Surv. Rev.
**2014**, 46, 155–166. [Google Scholar] [CrossRef] - Choy, S.; Zhang, S.; Lahaye, F.; Héroux, P. A comparison between GPS-only and combined GPS+GLONASS Precise Point Positioning. J. Spat. Sci.
**2013**, 58, 169–190. [Google Scholar] [CrossRef] - Mohammed, J.; Moore, T.; Hill, C.; Bingley, R.; Hansen, D. An assessment of static precise point positioning using GPS only, GLONASS only, and GPS plus GLONASS. Measurement
**2016**, 88, 121–130. [Google Scholar] [CrossRef] - Malik, J.S. Performance analysis of static precise point positioning using open-source GAMP. Artif. Satell. J. Planet. Geod.
**2020**, 55, 41–60. [Google Scholar] [CrossRef] - Hamed, M.; Abdallah, A.; Farah, A. Kinematic PPP using mixed GPS/GLONASS single-frequency observations. Artif. Satell.
**2019**, 54, 97–112. [Google Scholar] [CrossRef] - Deliktas, H.C. Investigation on the Contribution of GLONASS Observations to GPS Precise Point Positioning (PPP). Ph.D. Dissertation, The Ohio State University, Columbus, OH, USA, 2016. [Google Scholar]
- Li, P.; Zhang, X. Integrating GPS and GLONASS to accelerate convergence and initialization times of precise point positioning. GPS Solut.
**2014**, 18, 461–471. [Google Scholar] [CrossRef] - Li, X.; Ge, M.; Dai, X.; Ren, X.; Fritsche, M.; Wickert, J.; Schuh, H. Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo. J. Geod.
**2015**, 89, 607–635. [Google Scholar] [CrossRef] - Abd Rabbou, M.; El-Rabbany, A. Performance analysis of precise point positioning using multi-constellation GNSS: GPS, GLONASS, Galileo and BeiDou. Surv. Rev.
**2017**, 49, 39–50. [Google Scholar] [CrossRef] - Pan, L.; Zhang, X.; Li, X.; Li, X.; Lu, C.; Liu, J.; Wang, Q. Satellite availability and point positioning accuracy evaluation on a global scale for integration of GPS, GLONASS, BeiDou and Galileo. Adv. Space Res.
**2019**, 63, 2696–2710. [Google Scholar] [CrossRef] - Estey, L.H.; Meertens, C.M. TEQC: The multi-purpose toolkit for GPS/GLONASS data. GPS Solut.
**1999**, 3, 42–49. [Google Scholar] [CrossRef] - Dach, R.; Hugentobler, U.; Fridez, P.; Meindl, M. Bernese GPS Software Version 5.0; Astronomical Institute, University of Bern: Bern, Switzerland, 2007. [Google Scholar]
- Kouba, J. Implementation and testing of the gridded Vienna Mapping Function 1 (VMF1). J. Geod.
**2008**, 82, 193–205. [Google Scholar] [CrossRef] - re3data.org: VMF Data Server; Editing Status 2020-12-14; re3data.org-Registry of Research Data Repositories. Available online: https://www.re3data.org/repository/r3d100012025 (accessed on 26 July 2021).
- Gu, S.; Zheng, F.; Gong, X.; Lou, Y.; Shi, C. Fusing: A Distributed Software Platform for Real-Time High Precision Multi-GNSS Service; IGS Workshop: Wuhan, China, 2018. [Google Scholar]
- Lagler, K.; Schindelegger, M.; Böhm, J.; Krásná, H.; Nilsson, T. GPT2: Empirical slant delay model for radio space geodetic techniques. Geophys. Res. Lett.
**2013**, 40, 1069–1073. [Google Scholar] [CrossRef] [Green Version] - Dach, R.; Schmid, R.; Schmitz, M.; Thaller, D.; Schaer, S.; Lutz, S.; Steigenberger, P.; Wübbena, G.; Beutler, G. Improved antenna phase center models for GLONASS. GPS Solut.
**2011**, 15, 49–65. [Google Scholar] [CrossRef] - Liwosz, T. Effect of the GLONASS-specific receiver antenna phase center corrections on the results of European regional GNSS network. Artif. Satell.
**2013**, 48, 191. [Google Scholar] [CrossRef] - Wells, D.; Beck, N.; Kleusberg, A.; Krakiwsky, E.J.; Lachapelle, G.; Langley, R.B. Guide to GPS Positioning; Canadian GPS Assoc: Fredericton, NB, Canada, 1987. [Google Scholar]
- Noll, C.E. The crustal dynamics data information system: A resource to support scientific analysis using space geodesy. Adv. Space Res.
**2010**, 45, 1421–1440. [Google Scholar] [CrossRef] - Villiger, R. (Ed.) International GNSS Service Technical Report 2018 (IGS Annual Report); IGS Central Bureau and University of Bern; Bern Open Publishing: Bern, Switzerland, 2019. [Google Scholar]
- Gong, X.; Gu, S.; Zheng, F.; Wu, Q.; Liu, S.; Lou, Y. Improving GPS and Galileo precise data processing based on calibration of signal distortion biases. Measurement
**2021**, 174, 108981. [Google Scholar] [CrossRef]

**Figure 2.**The IGS tracking stations of the high (red triangle), middle (green triangle), and low latitude networks (blue triangle).

**Figure 4.**The average number of visible satellites of GPS, GLONASS, and GPS+GLONASS in the high (red), middle (green), and low (blue) latitude networks.

**Figure 5.**The histogram of visible satellites in the high (red), middle (green), and low (blue) latitude networks. The position of the dashed line and the value $\text{}{\mathrm{x}}^{-}$ indicate the average number of visible satellites. The ${\mathsf{\sigma}}^{2}$ represents the variance of the visible satellites’ distribution. Please note that the horizontal axis of GPS and GLONASS visible satellites differs from that of GPS+GLONASS.

**Figure 6.**The histogram of elevation distribution of the high (red), middle (green), and low (blue) latitude networks, the position of the dashed line and the value $\text{}{\mathrm{x}}^{-}$ indicate the mean elevation.

**Figure 7.**The PDOP of GPS, GLONASS, and GPS+GLONASS in the high (red), middle (green), and low (blue) latitude networks (The GLONASS PDOP for the low latitude network exceed the coordinate threshold, and the small picture in the upper right corner with the rose thread shows the full view of the PDOP).

Item | Processing Strategies |
---|---|

Signal selection | L1 and L2 |

Sampling rate | 30 s |

Elevation mask | 3° |

Precise products | CODE final precise products |

Weight for observations | Elevation-dependent weighting |

Receiver clock | Estimated as white noise |

Ionosphere | IF combination |

Troposphere | GPT2, VMF1 |

Ocean tidal loading | FES2004 |

DCB | CODE DCB monthly files |

Antenna center offset and variation | IGS14.atx |

Processing mode | PPP static in 24 h window |

Strategy | Forward extended Kalman filter |

Station Name | Receiver Type | Antenna + Radome Type |
---|---|---|

KIRU | SEPT POLARX5 | SEPCHOKE_B3E6 SPKE |

MAR7 | TRIMBLE ALLOY | LEIAR25.R3 LEIT |

METG | SEPT POLARX5 | TRM59800.00 SCIS |

NYA1 | TRIMBLE NETR8 | ASH701073.1 SNOW |

SOD3 | JAVAD TRE_3 DELTA | JAVRINGANT_DM SCIS |

SVTL | JAVAD TRE_3 DELTA | JAVRINGANT_DM JVDM |

TRO1 | TRIMBLE NETR9 | TRM59800.00 SCIS |

Station Name | Receiver Type | Antenna + Radome Type |
---|---|---|

AJAC | SEPT POLARX5 | TRM115000.00 NONE |

HERT | LEICA GRX1200GGPRO | LEIAT504GG NONE |

JOZE | SEPT POLARX5 | SEPCHOKE_B3E6 NONE |

MATG | LEICA GR10 | LEIAR25 NONE |

TLSG | SEPT POLARX5TR | TRM59800.00 NONE |

WARN | JAVAD TRE_3 DELTA | LEIAR25.R4 LEIT |

WTZR | LEICA GR50 | LEIAR25.R3 LEIT |

Station Name | Receiver Type | Antenna + Radome Type |
---|---|---|

BRAZ | TRIMBLE NETR9 | TRM57971.00 NONE |

CHPI | SEPT POLARX5 | TPSCR.G3 NONE |

SALU | TRIMBLE NETR9 | TRM115000.00 NONE |

SAVO | TRIMBLE NETR9 | TRM115000.00 NONE |

SPTU | TRIMBLE NETR9 | TRM57971.00 NONE |

TOPL | TRIMBLE NETR9 | TRM115000.00 NONE |

UFPR | TRIMBLE NETR9 | TRM115000.00 NONE |

Indicator | DI (%) | MP1 (m) | MP2 (m) | SN1 (dB) | SN2 (dB) | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|

Region | G | R | G | R | G | R | G | R | G | R | |

High latitude network | 94.33 | 82.37 | 0.47 | 0.48 | 0.45 | 0.39 | 6.56 | 7.12 | 5.33 | 6.88 | |

Middle latitude network | 96.11 | 83.46 | 0.39 | 0.46 | 0.39 | 0.43 | 7.02 | 7.20 | 6.35 | 6.76 | |

Low latitude network | 94.81 | 81.33 | 0.72 | 0.53 | 0.48 | 0.44 | 6.72 | 6.59 | 4.92 | 6.32 |

**Table 6.**The mean RMSE of coordinates of each network estimated with DD processing and their comparison among different processing modes (where R/G indicates the accuracy comparison of GLONASS and GPS results, (G + R)/G indicates the accuracy comparison of GPS+GLONASS results and GPS estimates. The positive red and negative green values indicate the percentage increment and reduction of accuracy, respectively).

System | G (mm) | R (mm) | G + R (mm) | R/G (%) | (G + R)/G (%) | |
---|---|---|---|---|---|---|

Component | ||||||

N | 2.99 | 2.58 | 2.27 | +13.79 | +24.29 | |

E | 1.38 | 1.60 | 1.38 | −16.17 | +0.00 | |

U | 9.87 | 9.24 | 9.41 | +6.35 | +4.66 | |

3D | 10.40 | 9.73 | 9.77 | +6.50 | +6.05 | |

N | 2.91 | 2.88 | 2.78 | +1.14 | +4.48 | |

E | 1.90 | 2.47 | 2.12 | −30.17 | −11.77 | |

U | 7.89 | 9.14 | 8.25 | −15.79 | −4.59 | |

3D | 8.62 | 9.89 | 8.96 | −14.74 | −3.96 | |

N | 2.60 | 3.18 | 2.57 | −22.13 | +1.37 | |

E | 2.94 | 4.79 | 2.87 | −62.86 | +2.39 | |

U | 7.77 | 10.74 | 6.93 | −38.24 | +10.89 | |

3D | 8.71 | 12.18 | 7.92 | −39.93 | +9.00 |

**Table 7.**The ambiguity fixing rate of DD processing (G, R, and G + R in black body denote the data processing mode, respectively. No bold G, R, and G + R represent the ambiguity fixing rate of GPS+GLONASS processing mode, respectively).

System | G (%) | R (%) | G + R | |||
---|---|---|---|---|---|---|

Region | G (%) | R (%) | G + R (%) | |||

High latitude network | 70.3 | 63.9 | 69 | 62.8 | 66.5 | |

Middle latitude network | 53.1 | 56 | 51.5 | 54.8 | 53.0 | |

Low latitude network | 74.7 | 26.4 | 74.6 | 33.9 | 57.5 |

**Table 8.**The mean RMSE of ZTDs estimated with DD processing for each network and their comparison between different processing modes (The positive red and negative green values indicate the percentage increment and reduction of accuracy, respectively).

System | G (mm) | R (mm) | G + R (mm) | R/G (%) | G + R/G (%) | |
---|---|---|---|---|---|---|

Region | ||||||

High latitude network | 4.70 | 5.45 | 4.80 | −15.85 | −2.08 | |

Middle latitude network | 5.63 | 6.32 | 5.57 | −12.26 | +1.06 | |

Low latitude network | 7.81 | 10.33 | 7.50 | −32.24 | +4.00 |

**Table 9.**The mean RMSE of coordinates for each network estimated with PPP and their comparison between different processing modes (The positive red and negative green values indicate the percentage increment and reduction of accuracy, respectively).

System | G (mm) | R (mm) | G + R (mm) | R/G (%) | G + R/G (%) | |
---|---|---|---|---|---|---|

Component | ||||||

N | 2.66 | 2.30 | 2.16 | +13.62 | +18.78 | |

E | 3.16 | 3.13 | 2.83 | +0.87 | +10.37 | |

U | 6.67 | 6.86 | 6.15 | −2.83 | +7.87 | |

3D | 7.92 | 8.03 | 7.18 | −1.37 | +9.35 | |

N | 2.97 | 3.56 | 3.14 | −19.83 | −5.63 | |

E | 2.64 | 3.21 | 2.56 | −21.77 | +2.99 | |

U | 7.54 | 9.08 | 7.62 | −20.40 | −1.03 | |

3D | 8.56 | 10.39 | 8.69 | −21.43 | −1.52 | |

N | 3.44 | 3.86 | 3.48 | −12.06 | −0.96 | |

E | 3.91 | 4.09 | 3.14 | −4.54 | +19.73 | |

U | 8.19 | 8.87 | 7.23 | −8.30 | +11.79 | |

3D | 9.78 | 10.52 | 8.66 | −7.58 | +11.40 |

**Table 10.**The mean convergence time of PPP for each network and their comparison between different processing modes (The red values indicate the percentage reduction of convergence time and the green values indicate the percentage increment of convergence time).

System | G (min) | R (min) | G + R (min) | R/G (%) | G + R/G (%) | |
---|---|---|---|---|---|---|

Region | ||||||

High latitude network | 14.26 | 21.66 | 13.39 | 51.90 | 6.11 | |

Middle latitude network | 16.81 | 24.43 | 14.03 | 45.28 | 16.57 | |

Low latitude network | 24.27 | 49.83 | 20.73 | 105.30 | 14.60 |

**Table 11.**The mean RMSE of ZTDs estimated with the PPP of each network and their comparison between different processing modes (The positive red and negative green values indicate the percentage increment and reduction of accuracy, respectively).

System | G (mm) | R (mm) | G + R (mm) | R/G (%) | G + R/G (%) | |
---|---|---|---|---|---|---|

Region | ||||||

High latitude network | 4.84 | 5.33 | 4.59 | −10.10 | +5.19 | |

Middle latitude network | 6.00 | 6.41 | 5.58 | −6.82 | +6.98 | |

Low latitude network | 8.23 | 9.39 | 7.59 | −14.08 | +7.79 |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Zheng, Y.; Zheng, F.; Yang, C.; Nie, G.; Li, S.
Analyses of GLONASS and GPS+GLONASS Precise Positioning Performance in Different Latitude Regions. *Remote Sens.* **2022**, *14*, 4640.
https://doi.org/10.3390/rs14184640

**AMA Style**

Zheng Y, Zheng F, Yang C, Nie G, Li S.
Analyses of GLONASS and GPS+GLONASS Precise Positioning Performance in Different Latitude Regions. *Remote Sensing*. 2022; 14(18):4640.
https://doi.org/10.3390/rs14184640

**Chicago/Turabian Style**

Zheng, Yanli, Fu Zheng, Cheng Yang, Guigen Nie, and Shuhui Li.
2022. "Analyses of GLONASS and GPS+GLONASS Precise Positioning Performance in Different Latitude Regions" *Remote Sensing* 14, no. 18: 4640.
https://doi.org/10.3390/rs14184640