Precise Point Positioning: Performances under Ionospheric Scintillations

The Precise Point Positioning (PPP) has become a powerful satellite
positioning technique which nearly equals performances provided by
advanced relative positioning techniques. Exploiting the growing
availability and quality of IGS products (satellite orbit and clock products),
the PPP technique can now provide a centimetre level solution in static
mode and a decimetre level in kinematic mode.
However, the PPP technique still presents some weaknesses. In order to
reach a high precision level, it requires a significant convergence period
which can typically reach 30 minutes under normal conditions. Moreover,
the PPP seems to be especially sensitive to ionospheric scintillations
effects which involve signal amplitude and phase variations of GNSS
signals. These weaknesses still limit the use of the PPP technique in the
frame of some specific and demanding applications (agricultural industry,
airborne mapping, etc.).
The goal of our research project is to develop new data processing
strategies attempting both to make the PPP technique more reliable under
ionospheric scintillations and to optimize the PPP convergence time. The
project is composed of several workpackages aiming to improve the
mentioned current PPP weaknesses with specific strategies.
One of the workpackages is devoted to the impact of satellite geometry on
PPP performances. Ionospheric scintillations are susceptible to reduce the
number of tracked satellites which degrades the quality of satellite
geometry. Based on an analytical development, we first attempt to figure
out what types of satellite geometry can be harmful. Then, we discuss
about the improvement of the satellite geometry quality involved by the
combined use of GPS and Galileo and its benefits in the frame of the PPP.
Another workpackage is related to the weighting scheme. Based on an
iterative least-square adjustment, the PPP algorithm requires the definition
of a stochastic model composed of an observation covariance matrix.
Usually, this matrix is chosen as diagonal with zero covariances assuming
that correlations between observations can be neglected. In particular, our
project aims to study the validity of this stochastic model for the PPP in
order to determine whether tuning the weighting scheme of the stochastic
model can improve the PPP performances. By exploiting spatial analysis
techniques, we try to characterize the spatial auto-correlation between
GNSS observations, considering the signal-to-noise ratio as the main
observable. From the results of these experiments, we will discuss about
the spatial correlation between GNSS observations both under normal
conditions and ionospheric scintillations.