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The DIA procedure can be integrated in two stage Kalman filter,
to extimate and correct cycle slips, as in (Lu, 1991).
5. THE SOFTWARE ALARIS
Several functions described in this paper and others are
implemented in the software ALARIS, mainly:
e Reference station:
o Raw biases estimation
o Ong way biases estimation, clock offset and drift,
atmospheric delays
o PRC and RRC estimation
o VRS generation
e Rover station:
o Static positioning
o Kinematic positioning
o Single or double frequency data processing
o Combined or non combined observation models
o Code observation processing for RT DGPS
o Residual bias estimation and recovering
e Real time quality control (DIA procedure) as described in
(Teunissen 1998, Tiberius 1998).
e Clock jump and cycle slip correction
e On The Fly ambiguity fixing to the nearest integer
e Satellite tracking with broadcast or precise ephemeredes
The software ALARIS is developed in FORTRANO0, and is
intended to perform kinematic positioning using a Multi
Reference Station approach. State space estimation is based on
Kalman filtering approach, by using standard, adaptive or two
stage Kalman filter algorithms.
ATROFC pr]
Figure 1. Tropospheric delay estimated over 24 hours
observations, collected by TORI reference station.
Figure 2. lonospheric delay estimated over 24 hours
observations, collected by TORI reference station.
6. CONCLUSIONS
The proposed algorithms are implemented in the software
ALARIS, that includes functions for real time applications or
data post processing, data quality control, bias estimation, for
static or kinematic positioning, differential or absolute point
positioning, in single or double frequency. Real time bias
estimation as been deeply investigated, mainly for atmospheric
biases reduction, in a multi station environment. The same state
space estimation approach has been used in the implemented
positioning algorithms, making possible the residual biases
estimation and recovering.
Undifferenced techniques are sensitive to the presence of errors
in the data, so is necessary to set up robust and noise adaptive
quality control procedures. The effects of outliers, cycle slips
and clock jump are been taken in account; moreover the local
detection test value can be used also as model correctness test.
These algorithms are then suitable to give good results in
permanent stations integrity monitoring and also in post
processing applications. The estimated biases have been used to
build an RTCM-like message. RTCM 2.x complete compatibility
is now under development.
The proposed methodology for biases estimation has at the
moment practical application problems, due to the necessity of
good ephemeris in real time and of a good oscillator to supply an
external frequency input to the reference station receiver. The
real time implementation has required the solution of problems
related to data transfer between the hardware components, slave,
master and rover stations, not yet completely concluded. The
real time estimation procedures have been optimized for memory
and processor requirements and for numerical stability.
The undifferenced approach take advantages from the
improvements in continental or global network real time
products, such as ephemeris or atmospheric models. On the
other side, can contribute to this improvement, that will be faster
with the upcoming modernized GNSS, leading also to better
performances in SBAS (Satellite Based Augmentation Systems)
and, as consequence, to better performances in real time also
with low cost equipments.
Finally, the real time GPS bias estimation can be useful in
: weather and space weather forecasting, and in time transfer
applications.