Publication Date:
2021-06-07
Description:
Global Navigation Satellite Systems (GNSS), in particular the Global Positioning System (GPS), have been widely used for high accuracy
geodetic positioning. The Least Squares functional models related to the GNSS observables have been more extensively studied than
the corresponding stochastic models, given that the development of the latter is significantly more complex. As a result, a simplified stochastic
model is often used in GNSS positioning, which assumes that all the GNSS observables are statistically independent and of the
same quality, i.e. a similar variance is assigned indiscriminately to all of the measurements. However, the definition of the stochastic model
may be approached from a more detailed perspective, considering specific effects affecting each observable individually, as for example the
effects of ionospheric scintillation. These effects relate to phase and amplitude fluctuations in the satellites signals that occur due to diffraction
on electron density irregularities in the ionosphere and are particularly relevant at equatorial and high latitude regions, especially
during periods of high solar activity. As a consequence, degraded measurement quality and poorer positioning accuracy may result.
This paper takes advantage of the availability of specially designed GNSS receivers that provide parameters indicating the level of phase
and amplitude scintillation on the signals, which therefore can be used to mitigate these effects through suitable improvements in the least
squares stochastic model. The stochastic model considering ionospheric scintillation effects has been implemented following the approach
described in Aquino et al. (2009), which is based on the computation of weights derived from the scintillation sensitive receiver tacking models
of Conker et al. (2003). The methodology and algorithms to account for these effects in the stochastic model are described and results of
experiments where GPS data were processed in both a relative and a point positioning mode are presented and discussed.
Two programs have been developed to enable the analyses: GPSeq (currently under development at the FCT/UNESP Sao Paulo State
University – Brazil) and PP_Sc (developed in a collaborative project between FCT/UNESP and Nottingham University – UK). The
point positioning approach is based on an epoch by epoch solution, whereas the relative positioning on an accumulated solution using
a Kalman Filter and the LAMBDA method to solve the Double Differences ambiguities. Additionally to the use of an improved stochastic
model, all data processing in this paper were performed using an option implemented in both programs, to estimate, for each
observable, an individual ionospheric parameter modelled as a stochastic process, using either the white noise or the random walk correlation
models. Data from a network of GPS Ionospheric Scintillation and TEC Monitor (GISTM) receivers set up in Northern Europe
as part of the ISACCO project (De Franceschi et al., 2006) were used in the experiments. The point positioning results have shown
improvements of the order of 45% in height accuracy when the proposed stochastic model is applied. In the static relative positioning,
improvements of the order of 50%, also in height accuracy, have been reached under moderate to strong scintillation conditions. These
and further results are discussed in this paper.
Description:
Published
Description:
1113 - 1121
Description:
3.9. Fisica della magnetosfera, ionosfera e meteorologia spaziale
Description:
5.4. Banche dati di geomagnetismo, aeronomia, clima e ambiente
Description:
JCR Journal
Description:
restricted
Keywords:
GNSS
;
GPS
;
Ionospheric scintillation
;
Receiver tracking models
;
Stochastic model
;
Relative and point positioning
;
01. Atmosphere::01.02. Ionosphere::01.02.05. Wave propagation
;
01. Atmosphere::01.02. Ionosphere::01.02.07. Scintillations
;
04. Solid Earth::04.03. Geodesy::04.03.08. Theory and Models
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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