Theory of GNSS Radio Occultation - GNSS Remote Sensing: Theory, Methods and Applications - page 109

Fig. 5.5 Data links used for
various differencing
technique
Geodesy (IGS) was formed in 1992, to oversee the deployment and operation of
a permanent global reference ground network to provide precise GPS orbits and
reference data to geodesists (Mueller and Beutler 1992 ). These reference data are
critical for the occultation missions.
For each occultation, the POD process consists of the orbit determination for the
occulting and reference GPS transmitters and for the LEO receiver. The POD of
GPS involves processing the ground reference stations data to estimate the high-
rate clock offsets and precise orbits for the GPS satellites. Once the ground-based
processing is completed, the space-based LEO POD processing is executed to solve
for the LEO orbits and clock offsets with several processing options, which includes
the dynamic approach, kinematic or geometric approach, and the reduced-dynamic
approach (e.g., Rim and Schutz 2002 ).
The dynamic orbit determination approach (Tapley 1973 ) directly solves for
the equation of the motion and thus requires precise models of the forces acting
on the satellite. This can be achieved by accurate modeling various forces on
the satellite, including the gravitational forces (e.g., gravitational effects of sun,
moon and planets, tides and relativistic effects), non-gravitational forces (e.g.,
atmospheric drag, solar and Earth radiation pressure and thermal radiation). Some
other unmodeled forces will generally need to be estimated. Dynamic model errors
are the limiting factor for this technique, which, however, can be reduced by the
continuous, global, and high precision GPS tracking data.
Alternatively, the kinematic approach doesn't require modeling the orbit dynam-
ics except for possible interpolation between solution points for the satellite (i.e.,
relies purely upon observation data), and the orbit solution is referenced to the
phase center of the on-board GPS antenna instead of the satellite's center of mass.
However, kinematic solutions are more sensitive to geometrical factors, such as the
direction of the GPS satellites and the GPS orbit accuracy, and they require the
resolution of phase ambiguities, which are not always available.
The reduced-dynamic approach (Wu et al. 1987 ), on the other hand, uses both
kinematic and dynamic information and optimally weighs their relative strength
by solving for local geometric position corrections using a process noise model
to absorb dynamic model errors.