An Improved GPS/GLONASS PPP Model for Kinematic Applications Title - - PowerPoint PPT Presentation
An Improved GPS/GLONASS PPP Model for Kinematic Applications Title goes here Mahmoud Abd Rabbou and Ahmed El-Rabbany Date | Presented by Department of Civil Engineering, Ryerson University Toronto, Canada Arab Institute of Navigation
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Date | Presented by
Mahmoud Abd Rabbou and Ahmed El-Rabbany
Department of Civil Engineering, Ryerson University Toronto, Canada Arab Institute of Navigation (AIN) Conference MELAHA 2014
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Introduction Problem statement Research objectives Mathematical models Results and analysis Conclusion
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The most common navigation systems are the Global Navigation Satellite System
(GNSS)
Commonly, kinematic precise point positioning (PPP) techniques employ un-
differenced ionosphere-free linear combination of GPS observations.
Precise point positioning (PPP) can potentially achieve centimeter- and decimeter-
level accuracy in static and kinematic modes, respectively, depending on the number and geometry of visible GPS satellites, and quality of observations.
However, GPS may not provide continuous solution in urban areas as a result of
limited satellite visibility.
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To overcome this limitation, we propose to combine the observation of GPS and
GLONASS systems.
The additional GLNOASS observations are expected to enhance the PPP accuracy
and solution availability, especially in dense urban areas where, in general, no sufficient number of GPS satellites are visible.
We take advantage of the full GLONASS constellation and the availability of
precise orbital and clock products produced by number of organizations, such as International GNSS Service (IGS).
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GPS/GLONASS PPP research has some limitations such as
The research is employed only un-differenced ionosphere-free PPP model
neglecting the latest advances in PPP techniques.
Most of the previous research is limited to the static PPP. The standalone GLONASS PPP accuracy is almost not investigated.
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To overcome the limitation mentioned before this research aims to develop a new
combined GPS/GLONASS PPP for precise positioning
Between-satellite-single-differnece (BSSD)ionosphere-free as well
as the traditional un-differenced ionosphere-free models are used,
Both
pseudorange and carrier phase GPS measurements are considered.
Standalone GLONASS
PPP accuracy in kinematic mode is investigated
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Un-differenced ionosphere-free linear combination equations
3 r s s G G r G G G G p1
P =ρ +c[dt +IFCD ]-c[dt
]+T +e
3 r s s R R r G R R R R R
P =ρ +c[dt +IFCD ]-c[dt
]+T +c[ISCB ]+e
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G
r s s r s G G r G G G G G
=ρ +c[dt +IFCD ]-c[dt
]+T +( N+IFBD -IFBD ) +
3 r s s r s R R r G R R R R R R
=ρ +c[dt +IFCD ]-c[dt
]+T +c[ISCB ]+( N+IFBD -IFBD ) +
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GPS satellite (l) is taken as a reference satellite to form between satellite single difference (BSSD) ionosphere-free linear combination;
3 kl s s kl kl kl G G G G G G
P =ρ -c[dt
] +T +e
3 nl s s nl nl nl R R R R R R R
P =ρ -c[dt
] +T +c[ISCB ]+e
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G
s s kl kl s kl kl G G G G G G
=ρ -c[dt
] +T +( N-IFBD ) +
3 s s nl nl s nl nl R R R R R R R R
=ρ -c[dt
] +T +c[ISCB ]+( N-IFBD ) +
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(Estimation filter)
1 1 1 1 1 1 1 k,k k,k k T k,k k,k k k,k
x x P P
1 1 1 1 1 1 T T k k,k k k k,k k k k k,k k k k k,k k k k ) k,k
K P H ( H P H R ) x x K ( Z H x ) P ( I K H P
Apply linearization to the nonlinear models using first order Tylor expansion and neglecting higher order terms. Restrict the probability distribution of measurement models to Gaussian distribution. Prediction step Update step
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combined GPS/GLONASS-PPP models.
December 12, 2012 (DOY 347), under challenging scenarios for satellite navigation availability.
differential GNSS (DGNSS) solution.
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GPS/GLONASS positioning accuracy using un-differenced ionosphere- free model
precision are improved by adding GLONASS observations.
less accuracy than GPS-PPP solution.
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GPS/GLONASS positioning accuracy using BSSD ionosphere-free model
accuracy
BSSD ionosphere-free model is better than that
un-differenced model
GPS-only PPP and GNSS-PPP while no significant improvements for GLONASS- PPP.
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Statistical parameters for various GNSS model combinations. PPP-model Un-differenced Ionosphere-free PPP GNSS Sys: GPS+GLONASS GPS GLONASS Positioning latitude longitude altitude latitude longitude altitude latitude longitude altitude mean(m)
0.034 0.010 0.003 0.099 0.110
0.010 0.222 max(m) 0.103 0.146 0.238 0.091 0.232 0.268 0.030 0.252 0.420 min(m)
0.037 RMSE(m) 0.051 0.064 0.082 0.045 0.113 0.133 0.079 0.075 0.230 PPP-model BSSD Ionosphere-free PPP GNSS Sys: GPS+GLONASS GPS GLONASS Positioning latitude longitude altitude latitude longitude altitude latitude longitude altitude mean(m)
0.039 0.029
0.014 0.176 max(m) 0.105 0.084 0.075 0.095 0.172 0.255 0.098 0.236 0.339 min(m)
RMSE(m) 0.045 0.038 0.074 0.050 0.072 0.093 0.053 0.073 0.188
By comparing the mean and the RMSE, the positioning precision is generally improved when GLONASS observations are added. Also the positioning results of BSSD model are more precise than that of the traditional un-differenced model.
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CONCLUSION
The performance of combined GPS/GLONASS PPP model in kinematic mode has
been investigated.
Three
GNSS PPP models have been considered, namely GPS-only and GLONASS-only and, combined GPS/GLONASS PPP.
Both
un-differenced and BSSD ionosphere-free linear combinations are processed.
It
has been shown that utilizing BSSD ionosphere model enhances the positioning accuracy and precision generally in the standalone GPS and the combined GPS and GLONASS-PPP, while no significant improvements in the GLONASS-PPP is shown.
GLONASS-PPP
positioning solution shows that positioning accuracy and precision are less than the GPS PPP due to the limited number of GLONASS satellites available compared with GPS.
The results also clearly show the addition of GLONASS satellites observations
generally improved the positioning accuracy compared to GPS only PPP.
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