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Performance Analysis of Several GPS/Galileo Precise Point Positioning Models.

Afifi A, El-Rabbany A - Sensors (Basel) (2015)

Bottom Line: In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model.As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model.Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada. akram.afifi@ryerson.ca.

ABSTRACT
This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage of the IGS-MGEX network products to correct for the satellite differential code biases and the orbital and satellite clock errors. Natural Resources Canada's GPSPace PPP software is modified to handle the various GPS/Galileo PPP models. A total of six data sets of GPS and Galileo observations at six IGS stations are processed to examine the performance of the various PPP models. It is shown that the traditional un-differenced GPS/Galileo PPP model, the GPS decoupled clock model, and the semi-decoupled clock GPS/Galileo PPP model improve the convergence time by about 25% in comparison with the un-differenced GPS-only model. In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model. Moreover, the BSSD GPS/Galileo PPP model improves the solution convergence time by about 50%, in comparison with the un-differenced GPS PPP model, regardless of the type of BSSD combination used. As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model. Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference.

No MeSH data available.


Analysis stations.
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sensors-15-14701-f006: Analysis stations.

Mentions: To verify the introduced GPS/Galileo PPP models, GPS/Galileo measurements at six well-distributed stations (Figure 6) were selected from the IGS tracking network [23]. Those stations are occupied by GNSS receivers, which are capable of simultaneously tracking the GPS/Galileo constellations. The positioning results for station DLF1 are presented below. Similar results are obtained from the other stations. However, a summary of the convergence times and precision are presented below for all stations. Natural Resources Canada (NRCan) GPSPace PPP software was modified to enable a GPS/Galileo PPP solution as described above. A solution is considered to be converged when the three-dimensional positioning standard deviation reaches 10 cm. The sampling interval for all data sets is 30 s of 5 April 2013, while the time span used in the analysis is one hour, which is selected to ensure that the four Galileo satellites are visible at each station.


Performance Analysis of Several GPS/Galileo Precise Point Positioning Models.

Afifi A, El-Rabbany A - Sensors (Basel) (2015)

Analysis stations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507674&req=5

sensors-15-14701-f006: Analysis stations.
Mentions: To verify the introduced GPS/Galileo PPP models, GPS/Galileo measurements at six well-distributed stations (Figure 6) were selected from the IGS tracking network [23]. Those stations are occupied by GNSS receivers, which are capable of simultaneously tracking the GPS/Galileo constellations. The positioning results for station DLF1 are presented below. Similar results are obtained from the other stations. However, a summary of the convergence times and precision are presented below for all stations. Natural Resources Canada (NRCan) GPSPace PPP software was modified to enable a GPS/Galileo PPP solution as described above. A solution is considered to be converged when the three-dimensional positioning standard deviation reaches 10 cm. The sampling interval for all data sets is 30 s of 5 April 2013, while the time span used in the analysis is one hour, which is selected to ensure that the four Galileo satellites are visible at each station.

Bottom Line: In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model.As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model.Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada. akram.afifi@ryerson.ca.

ABSTRACT
This paper examines the performance of several precise point positioning (PPP) models, which combine dual-frequency GPS/Galileo observations in the un-differenced and between-satellite single-difference (BSSD) modes. These include the traditional un-differenced model, the decoupled clock model, the semi-decoupled clock model, and the between-satellite single-difference model. We take advantage of the IGS-MGEX network products to correct for the satellite differential code biases and the orbital and satellite clock errors. Natural Resources Canada's GPSPace PPP software is modified to handle the various GPS/Galileo PPP models. A total of six data sets of GPS and Galileo observations at six IGS stations are processed to examine the performance of the various PPP models. It is shown that the traditional un-differenced GPS/Galileo PPP model, the GPS decoupled clock model, and the semi-decoupled clock GPS/Galileo PPP model improve the convergence time by about 25% in comparison with the un-differenced GPS-only model. In addition, the semi-decoupled GPS/Galileo PPP model improves the solution precision by about 25% compared to the traditional un-differenced GPS/Galileo PPP model. Moreover, the BSSD GPS/Galileo PPP model improves the solution convergence time by about 50%, in comparison with the un-differenced GPS PPP model, regardless of the type of BSSD combination used. As well, the BSSD model improves the precision of the estimated parameters by about 50% and 25% when the loose and the tight combinations are used, respectively, in comparison with the un-differenced GPS-only model. Comparable results are obtained through the tight combination when either a GPS or a Galileo satellite is selected as a reference.

No MeSH data available.