scholarly journals GPS AND GLONASS COMBINED STATIC PRECISE POINT POSITIONING (PPP)

2016 ◽  
Vol XLI-B1 ◽  
pp. 483-488
Author(s):  
D. Pandey ◽  
R. Dwivedi ◽  
O. Dikshit ◽  
A. K. Singh
Keyword(s):  
Precise Point Positioning ◽  
Rapid Development ◽  
Three Dimensional ◽  
Global Navigation Satellite Systems ◽  
Open Pit ◽  
Positioning Accuracy ◽  
Dilution Of Precision ◽  
Satellite Visibility ◽  
Point Positioning ◽  
Gps Observations

With the rapid development of multi-constellation Global Navigation Satellite Systems (GNSSs), satellite navigation is undergoing drastic changes. Presently, more than 70 satellites are already available and nearly 120 more satellites will be available in the coming years after the achievement of complete constellation for all four systems- GPS, GLONASS, Galileo and BeiDou. The significant improvement in terms of satellite visibility, spatial geometry, dilution of precision and accuracy demands the utilization of combining multi-GNSS for Precise Point Positioning (PPP), especially in constrained environments. Currently, PPP is performed based on the processing of only GPS observations. Static and kinematic PPP solutions based on the processing of only GPS observations is limited by the satellite visibility, which is often insufficient for the mountainous and open pit mines areas. One of the easiest options available to enhance the positioning reliability is to integrate GPS and GLONASS observations. This research investigates the efficacy of combining GPS and GLONASS observations for achieving static PPP solution and its sensitivity to different processing methodology. Two static PPP solutions, namely standalone GPS and combined GPS-GLONASS solutions are compared. The datasets are processed using the open source GNSS processing environment <i>gLAB</i> 2.2.7 as well as <i>magicGNSS</i> software package. The results reveal that the addition of GLONASS observations improves the static positioning accuracy in comparison with the standalone GPS point positioning. Further, results show that there is an improvement in the three dimensional positioning accuracy. It is also shown that the addition of GLONASS constellation improves the total number of visible satellites by more than 60% which leads to the improvement of satellite geometry represented by Position Dilution of Precision (PDOP) by more than 30%.

scholarly journals GPS AND GLONASS COMBINED STATIC PRECISE POINT POSITIONING (PPP)

2016 ◽  
Vol XLI-B1 ◽  
pp. 483-488 ◽  
Author(s):  
D. Pandey ◽  
R. Dwivedi ◽  
O. Dikshit ◽  
A. K. Singh
Keyword(s):  
Precise Point Positioning ◽  
Rapid Development ◽  
Three Dimensional ◽  
Global Navigation Satellite Systems ◽  
Open Pit ◽  
Positioning Accuracy ◽  
Dilution Of Precision ◽  
Satellite Visibility ◽  
Point Positioning ◽  
Gps Observations

With the rapid development of multi-constellation Global Navigation Satellite Systems (GNSSs), satellite navigation is undergoing drastic changes. Presently, more than 70 satellites are already available and nearly 120 more satellites will be available in the coming years after the achievement of complete constellation for all four systems- GPS, GLONASS, Galileo and BeiDou. The significant improvement in terms of satellite visibility, spatial geometry, dilution of precision and accuracy demands the utilization of combining multi-GNSS for Precise Point Positioning (PPP), especially in constrained environments. Currently, PPP is performed based on the processing of only GPS observations. Static and kinematic PPP solutions based on the processing of only GPS observations is limited by the satellite visibility, which is often insufficient for the mountainous and open pit mines areas. One of the easiest options available to enhance the positioning reliability is to integrate GPS and GLONASS observations. This research investigates the efficacy of combining GPS and GLONASS observations for achieving static PPP solution and its sensitivity to different processing methodology. Two static PPP solutions, namely standalone GPS and combined GPS-GLONASS solutions are compared. The datasets are processed using the open source GNSS processing environment <i>gLAB</i> 2.2.7 as well as <i>magicGNSS</i> software package. The results reveal that the addition of GLONASS observations improves the static positioning accuracy in comparison with the standalone GPS point positioning. Further, results show that there is an improvement in the three dimensional positioning accuracy. It is also shown that the addition of GLONASS constellation improves the total number of visible satellites by more than 60% which leads to the improvement of satellite geometry represented by Position Dilution of Precision (PDOP) by more than 30%.

scholarly journals Performance Analysis of Static Precise Point Positioning Using Open-Source GAMP

2020 ◽  
Vol 55 (2) ◽  
pp. 41-60
Author(s):  
Jabir Shabbir Malik
Keyword(s):  
Performance Analysis ◽  
Open Source ◽  
Observational Data ◽  
Precise Point Positioning ◽  
Three Dimensional ◽  
Satellite System ◽  
International Gnss Service ◽  
Positioning Accuracy ◽  
Position Accuracy ◽  
Point Positioning

AbstractIn addition to Global Positioning System (GPS) constellation, the number of Global Navigation Satellite System (GLONASS) satellites is increasing; it is now possible to evaluate and analyze the position accuracy with both the GPS and GLONASS constellation. In this article, statistical analysis of static precise point positioning (PPP) using GPS-only, GLONASS-only, and combined GPS/GLONASS modes is evaluated. Observational data of 10 whole days from 10 International GNSS Service (IGS) stations are used for analysis. Position accuracy in east, north, up components, and carrier phase/code residuals is analyzed. Multi-GNSS PPP open-source package is used for the PPP performance analysis. The analysis also provides the GNSS researchers the understanding of the observational data processing algorithm. Calculation statistics reveal that standard deviation (STD) of horizontal component is 3.83, 13.80, and 3.33 cm for GPS-only, GLONASS-only, and combined GPS/GLONASS PPP solutions, respectively. Combined GPS/GLONASS PPP achieves better positioning accuracy in horizontal and three-dimensional (3D) accuracy compared with GPS-only and GLONASS-only PPP solutions. The results of the calculation show that combined GPS/GLONASS PPP improves, on an average, horizontal accuracy by 12.11% and 60.33% and 3D positioning accuracy by 10.39% and 66.78% compared with GPS-only and GLONASS-only solutions, respectively. In addition, the results also demonstrate that GPS-only solutions show an improvement of 54.23% and 62.54% compared with GLONASS-only PPP mode in horizontal and 3D components, respectively. Moreover, residuals of GLONASS ionosphere-free code observations are larger than the GPS code residuals. However, phase residuals of GPS and GLONASS phase observations are of the same magnitude.

scholarly journals GPS/BDS-2/Galileo Precise Point Positioning Ambiguity Resolution Based on the Uncombined Model

2020 ◽  
Vol 12 (11) ◽  
pp. 1853
Author(s):  
Jin Wang ◽  
Guanwen Huang ◽  
Qin Zhang ◽  
Yang Gao ◽  
Yuting Gao ◽  
...  
Keyword(s):  
Ambiguity Resolution ◽  
Precise Point Positioning ◽  
Three Dimensional ◽  
Convergence Time ◽  
Wide Lane ◽  
3D Positioning ◽  
System Bias ◽  
Point Positioning ◽  
Raw Observations ◽  
Gps Observations

In this study, an uncombined precise point positioning (PPP) model was established and was used for estimating fractional cycle bias (FCB) products and for achieving ambiguity resolution (AR), using GPS, BDS-2, and Galileo raw observations. The uncombined PPP model is flexible and efficient for positioning services and generating FCB. The FCBs for GPS, BDS-2, and Galileo were estimated using the uncombined PPP model with observations from the Multi-GNSS Experiment (MGEX) stations. The root mean squares (RMSs) of the float ambiguity a posteriori residuals associated with all of the three GNSS constellations, i.e., GPS, BDS-2, and Galileo, are less than 0.1 cycles for both narrow-lane (NL) and wide-lane (WL) combinations. The standard deviation (STD) of the WL combination FCB series is 0.015, 0.013, and 0.006 cycles for GPS, BDS-2, and Galileo, respectively, and the counterpart for the NL combination FCB series is 0.030 and 0.0184 cycles for GPS and Galileo, respectively. For the BDS-2 NL combination FCB series, the STD of the inclined geosynchronous orbit (IGSO) satellites is 0.0156 cycles, while the value for the medium Earth orbit (MEO) satellites is 0.073 cycles. The AR solutions produced by the uncombined multi-GNSS PPP model were evaluated from the positioning biases and the success fixing rate of ambiguity. The experimental results demonstrate that the growth of the amount of available satellites significantly improves the PPP performance. The three-dimensional (3D) positioning accuracies associated with the PPP ambiguity-fixed solutions for the respective only-GPS, GPS/BDS-2, GPS/Galileo, and GPS/BDS-2/Galileo models are 1.34, 1.19, 1.21, and 1.14 cm, respectively, and more than a 30% improvement is achieved when compared to the results related to the ambiguity-float solutions. Additionally, the convergence time based on the GPS/BDS-2/Galileo observations is only 7.5 min for the ambiguity-fixed solutions, and the results exhibit a 53% improvement in comparison to the ambiguity-float solutions. The values of convergence time based on the only-GPS observations are estimated as 22 and 10.5 min for the ambiguity-float and ambiguity-fixed solutions, respectively. Lastly, the success fixing rate of ambiguity is also dramatically raised for the multi-GNSS PPP AR. For example, the percentage is approximately 99% for the GPS/BDS-2/Galileo solution over a 10 min processing period. In addition, the inter-system bias (ISB) between GPS, BDS-2, and Galileo, which is carefully considered in the uncombined multi-GNSS PPP method, is modeled as a white noise process. The differences of the ISB series between BDS-2 and Galileo indicate that the clock datum bias of the satellite clock offset estimation accounts for the variation of the ISB series.

scholarly journals Study on Multi-GNSS Precise Point Positioning Performance with Adverse Effects of Satellite Signals on Android Smartphone

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6447
Author(s):  
Hongyu Zhu ◽  
Linyuan Xia ◽  
Dongjin Wu ◽  
Jingchao Xia ◽  
Qianxia Li
Keyword(s):  
Adverse Effects ◽  
Precise Point Positioning ◽  
Phase Error ◽  
Three Dimensional ◽  
Satellite System ◽  
Dual Frequency ◽  
Positioning Accuracy ◽  
Noise Ratio ◽  
Point Positioning ◽  
Gnss Observations

The emergence of dual frequency global navigation satellite system (GNSS) chip actively promotes the progress of precise point positioning (PPP) technology in Android smartphones. However, some characteristics of GNSS signals on current smartphones still adversely affect the positioning accuracy of multi-GNSS PPP. In order to reduce the adverse effects on positioning, this paper takes Huawei Mate30 as the experimental object and presents the analysis of multi-GNSS observations from the aspects of carrier-to-noise ratio, cycle slip, gradual accumulation of phase error, and pseudorange residual. Accordingly, we establish a multi-GNSS PPP mathematical model that is more suitable for GNSS observations from a smartphone. The stochastic model is composed of GNSS step function variances depending on carrier-to-noise ratio, and the robust Kalman filter is applied to parameter estimation. The multi-GNSS experimental results show that the proposed PPP method can significantly reduce the effect of poor satellite signal quality on positioning accuracy. Compared with the conventional PPP model, the root mean square (RMS) of GPS/BeiDou (BDS)/GLONASS static PPP horizontal and vertical errors in the initial 10 min decreased by 23.71% and 62.06%, respectively, and the horizontal positioning accuracy reached 10 cm within 100 min. Meanwhile, the kinematic PPP maximum three-dimensional positioning error of GPS/BDS/GLONASS decreased from 16.543 to 10.317 m.

scholarly journals Changes in the GNSS precise point positioning accuracy during a strong geomagnetic storm

2020 ◽  
Vol 196 ◽  
pp. 01001
Author(s):  
Anna Yasyukevich ◽  
Semen Syrovatskii ◽  
Yury Yasyukevich
Keyword(s):  
Geomagnetic Storm ◽  
Precise Point Positioning ◽  
Global Navigation Satellite Systems ◽  
Maximum Effect ◽  
Electron Content ◽  
Dual Frequency ◽  
Period Range ◽  
Positioning Accuracy ◽  
Total Electron ◽  
Point Positioning

Based on the data from dual-frequency receivers of global navigation satellite systems (GNSS), we analyze the changes in GNSS positioning accuracy during the August 25-26, 2018 strong geomagnetic storm on a global scale. The storm is one of the strongest geomagnetic events of the solar cycle 24. To analyze the positioning quality, we calculated coordinates using the precise point positioning (PPP) method in the kinematic mode. We recorder a significant degradation in the PPP positioning accuracy during the main phase of the storm. The maximum effect is observed in the middle and high latitudes of the US-Atlantic longitude sector. The average PPP error during the storm is shown to exceed ~0.5 m, that is up to 5 times higher than the values typical on quiet days. Areas with increased PPP errors is revealed to correspond to the regions with significant increase in the intensity of total electron content variations of 10–20 min period range. This increase is presumably due to the auroral oval expansion toward middle latitudes.

The Effect of the State-of-the-Art Mapping Functions on Precise Point Positioning

2020 ◽  
Author(s):  
Faruk Can Durmus ◽  
Bahattin Erdogan
Keyword(s):  
Water Vapor ◽  
Precise Point Positioning ◽  
State Of The Art ◽  
Mapping Function ◽  
Empirical Models ◽  
Global Navigation Satellite Systems ◽  
Tropospheric Delay ◽  
Positioning Accuracy ◽  
Mapping Functions ◽  
Point Positioning

&lt;p&gt;Global Navigation Satellite Systems (GNSS) are effectively used for different applications of Geomatic Engineering. There are lots of model error sources that affect the performance of the point positioning. Especially for the Precise Point Positioning (PPP) technique, which depends on the absolute point positioning, these errors should be modelled since PPP technique utilizes un-differenced and ionosphere-free combinations. Studies about PPP technique show that the effect of tropospheric delay caused by water vapor and dry air in the troposphere, which affects GNSS signals, is an important parameter should be modelled. Total zenith delay consists of both hydrostatic and wet delay. Hydrostatic delay can be accurately estimated by using atmospheric surface pressure and temperature with empirical models. Although there are many empirical models currently used for the determination of the zenith wet delay, the accuracies of these models are inadequate due to the temporal and spatial variation of atmospheric water vapor. Moreover, the tropospheric delay occurs along the path of GNSS signals and the Mapping Functions (MFs) are used to convert the tropospheric signal delay along the zenith direction to the slant direction. In this study, it is aimed to measure the effect of the globally produced MFs as Niell Mapping Function (NMF), Vienna Mapping Function 1 (VMF1), Global Mapping Function (GMF) and Global Pressure Temperature model 2 (GPT2) for GNSS positioning accuracy. Only GPS satellite system has been taken into account. For the analysis it has planned to process approximately 294 permanent stations from Crustal Dynamics Data Information System (CDDIS) archive with Jet Propulsion Laboratory&amp;#8217;s GipsyX v1.2 software. In order to reveal the effect of different season the GPS observations in January, April, July and October, 2018 have been obtained. The solutions were derived for different session durations as 2, 4, 6, 8, 12 and 24 hours for each global MFs and root mean square values have been estimated for each session durations. According to the first results that based on the six points, which the ellipsoidal heights of them are between 20 m and 105 m, although the results of north and east components are close to each other; the results of VMF1 are better than other global MFs for up component.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt;: State-of-the-Art Mapping Function, Troposphere, Precise Point Positioning, Accuracy, GipsyX&lt;/p&gt;

The Effect of the State-of-the-Art Mapping Functions on Precise Point Positioning

2021 ◽  
Author(s):  
Faruk Can Durmus ◽  
Bahattin Erdogan
Keyword(s):  
Water Vapor ◽  
Precise Point Positioning ◽  
State Of The Art ◽  
Mapping Function ◽  
Empirical Models ◽  
Global Navigation Satellite Systems ◽  
Tropospheric Delay ◽  
Positioning Accuracy ◽  
Mapping Functions ◽  
Point Positioning

&lt;p&gt;Global Navigation Satellite Systems (GNSS) are effectively used for different applications of Geomatic Engineering. There are lots of model error sources that affect the performance of the point positioning. Especially for the Precise Point Positioning (PPP) technique, which depends on the absolute point positioning, these errors should be modelled since PPP technique utilizes un-differenced and ionosphere-free combinations. Studies about PPP technique show that the effect of tropospheric delay caused by water vapor and dry air in the troposphere, which affects GNSS signals, is an important parameter should be modelled. Total zenith delay consists of both hydrostatic and wet delay. Hydrostatic delay can be accurately estimated by using atmospheric surface pressure and height with empirical models. Although there are many empirical models currently used for the determination of the zenith wet delay, the accuracies of these models are inadequate due to the temporal and spatial variation of atmospheric water vapor. Moreover, the tropospheric delay occurs along the path of GNSS signals and the Mapping Functions (MFs) are used to convert the tropospheric signal delay along the zenith direction to the slant direction. In this study, it is aimed to measure the effect of the globally produced MFs as Niell Mapping Function (NMF), Vienna Mapping Function 1 (VMF1), Global Mapping Function (GMF) and Global Pressure Temperature model 2 (GPT2) for GNSS positioning accuracy. Only GPS satellite system has been taken into account. For the analysis it has planned to process approximately 294 permanent stations from Crustal Dynamics Data Information System (CDDIS) archive with Jet Propulsion Laboratory&amp;#8217;s GipsyX v1.2 software. In order to reveal the effect of different season the GPS observations in January, April, July and October, 2018 have been obtained. The solutions were derived for different session durations as 2, 4, 6, 8, 12 and 24 hours for each global MFs and root mean square values have been estimated for each session durations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt;: State-of-the-Art Mapping Function, Troposphere, Precise Point Positioning, Accuracy, GipsyX&lt;/p&gt;

scholarly journals Precise point positioning with GPS and Galileo broadcast ephemerides

GPS Solutions ◽  
2021 ◽  
Vol 25 (2) ◽  
Author(s):  
Luca Carlin ◽  
André Hauschild ◽  
Oliver Montenbruck
Keyword(s):  
Precise Point Positioning ◽  
Three Dimensional ◽  
Test Results ◽  
Process Noise ◽  
Functional Models ◽  
Ambiguity Estimation ◽  
Point Positioning ◽  
And Performance ◽  
Range Error ◽  
Space Range

AbstractFor more than 20 years, precise point positioning (PPP) has been a well-established technique for carrier phase-based navigation. Traditionally, it relies on precise orbit and clock products to achieve accuracies in the order of centimeters. With the modernization of legacy GNSS constellations and the introduction of new systems such as Galileo, a continued reduction in the signal-in-space range error (SISRE) can be observed. Supported by this fact, we analyze the feasibility and performance of PPP with broadcast ephemerides and observations of Galileo and GPS. Two different functional models for compensation of SISREs are assessed: process noise in the ambiguity states and the explicit estimation of a SISRE state for each channel. Tests performed with permanent reference stations show that the position can be estimated in kinematic conditions with an average three-dimensional (3D) root mean square (RMS) error of 29 cm for Galileo and 63 cm for GPS. Dual-constellation solutions can further improve the accuracy to 25 cm. Compared to standard algorithms without SISRE compensation, the proposed PPP approaches offer a 40% performance improvement for Galileo and 70% for GPS when working with broadcast ephemerides. An additional test with observations taken on a boat ride yielded 3D RMS accuracy of 39 cm for Galileo, 41 cm for GPS, and 27 cm for dual-constellation processing compared to a real-time kinematic reference solution. Compared to the use of process noise in the phase ambiguity estimation, the explicit estimation of SISRE states yields a slightly improved robustness and accuracy at the expense of increased algorithmic complexity. Overall, the test results demonstrate that the application of broadcast ephemerides in a PPP model is feasible with modern GNSS constellations and able to reach accuracies in the order of few decimeters when using proper SISRE compensation techniques.

scholarly journals Multi-GNSS Combined Precise Point Positioning Using Additional Observations with Opposite Weight for Real-Time Quality Control

2019 ◽  
Vol 11 (3) ◽  
pp. 311 ◽  
Author(s):  
Wenju Fu ◽  
Guanwen Huang ◽  
Yuanxi Zhang ◽  
Qin Zhang ◽  
Bobin Cui ◽  
...  
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Precise Point Positioning ◽  
Satellite System ◽  
Convergence Time ◽  
Navigation Satellite ◽  
Positioning Accuracy ◽  
Global Navigation ◽  
Point Positioning ◽  
Global Navigation Satellite

The emergence of multiple global navigation satellite systems (multi-GNSS), including global positioning system (GPS), global navigation satellite system (GLONASS), Beidou navigation satellite system (BDS), and Galileo, brings not only great opportunities for real-time precise point positioning (PPP), but also challenges in quality control because of inevitable data anomalies. This research aims at achieving the real-time quality control of the multi-GNSS combined PPP using additional observations with opposite weight. A robust multiple-system combined PPP estimation is developed to simultaneously process observations from all the four GNSS systems as well as single, dual, or triple systems. The experiment indicates that the proposed quality control can effectively eliminate the influence of outliers on the single GPS and the multiple-system combined PPP. The analysis on the positioning accuracy and the convergence time of the proposed robust PPP is conducted based on one week’s data from 32 globally distributed stations. The positioning root mean square (RMS) error of the quad-system combined PPP is 1.2 cm, 1.0 cm, and 3.0 cm in the east, north, and upward components, respectively, with the improvements of 62.5%, 63.0%, and 55.2% compared to those of single GPS. The average convergence time of the quad-system combined PPP in the horizontal and vertical components is 12.8 min and 12.2 min, respectively, while it is 26.5 min and 23.7 min when only using single-GPS PPP. The positioning performance of the GPS, GLONASS, and BDS (GRC) combination and the GPS, GLONASS, and Galileo (GRE) combination is comparable to the GPS, GLONASS, BDS and Galileo (GRCE) combination and it is better than that of the GPS, BDS, and Galileo (GCE) combination. Compared to GPS, the improvements of the positioning accuracy of the GPS and GLONASS (GR) combination, the GPS and Galileo (GE) combination, the GPS and BDS (GC) combination in the east component are 53.1%, 43.8%, and 40.6%, respectively, while they are 55.6%, 48.1%, and 40.7% in the north component, and 47.8%, 40.3%, and 34.3% in the upward component.

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