1
International Global Navigation Satellite Systems Association
IGNSS Symposium 2018
Colombo Theatres, Kensington Campus, UNSW Australia
7 – 9 February 2018
A New Model for Precise Point Positioning to
Improve Fault Detection
Ahmed El-Mowafy
Department of Spatial Sciences, Curtin University, Australia
(Email: a.el-mowafy@curtin.edu.au)
ABSTRACT
The availability of real-time corrections to broadcast satellite orbits and
clock offset enables implementation of real-time Precise Point Positioning
(RT-PPP) in important applications such as natural hazard warning systems
and intelligent transport systems. However, current RT-PPP models combine
the observations with the orbit and clock corrections in one term.
Accordingly, faults in these corrections, for instance due to spoofing, will
result in exclusion of their related satellite measurements, which would lead
to degradation of the positioning quality, with a total disabling of RT-PPP if
errors are introduced in all corrections.
In this contribution, a new PPP model that treats the corrections to broadcast
orbit and clock offset as quasi-observations is presented. This model enables
fault detection and exclusion of these corrections separate from the
observations. The excluded faulty corrections can be replaced by predicted
values, using for instance the predicted IGS ultra-rapid orbits, and a linear
polynomial with sinusoid terms for the clock corrections. Thus, the method
preserves positioning by keeping the measurements that have faulty
corrections, and using them along with the predicted corrections. The
proposed method is validated at three IGS stations, where its results was
compared to results of the traditional PPP methodology. Artificial faults
were inserted at random events and the test was repeated with a varying
number of faults. Results show that using the proposed method, positioning
was maintained during the faulted periods, whereas the traditional PPP
accuracy degraded sharply with the increase of number of faults.
KEYWORDS: PPP, GNSS, Real-time positioning, Fault Detection and Exclusion (FDE)