A realistic and easy-to-implement weighting model for GNSS phase observations

Observation weighting is an essential component of GPS stochastic modeling and plays a key role in reliable outlier detection and parameter estimation. Nowadays, satellite elevation angle and SNR are used as quality indicators for GPS phase measurements in high-accuracy geodetic applications. In com...

Full description

Bibliographic Details
Main Authors: Luo, X., Mayer, M., Heck, B., Awange, Joseph
Format: Journal Article
Published: IEEE Geoscience and Remote Sensing Society 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/35912
_version_ 1848754624084836352
author Luo, X.
Mayer, M.
Heck, B.
Awange, Joseph
author_facet Luo, X.
Mayer, M.
Heck, B.
Awange, Joseph
author_sort Luo, X.
building Curtin Institutional Repository
collection Online Access
description Observation weighting is an essential component of GPS stochastic modeling and plays a key role in reliable outlier detection and parameter estimation. Nowadays, satellite elevation angle and SNR are used as quality indicators for GPS phase measurements in high-accuracy geodetic applications. In comparison with elevation-dependent models, SNR-based weighting schemes represent the reality better, but usually require greater implementation efforts. Relying upon a representative analysis of empirical SNR-based weights, this paper proposes the elevation-dependent exponential weighting function EXPZ, which benefits from realistic SNR-based weights and enables easy software implementation. To process GPS data from a regional network, this advanced weighting scheme is implemented in the Bernese GPS Software 5.0 and is compared with the conventional elevation-dependent COSZ model in terms of phase ambiguity resolution, troposphere parameter (TRP) estimation, and site coordinate determination. The results show that the proposed EXPZ model significantly attenuates the downweighting effects on low-elevation observations and improves the success rates of ambiguity resolution by about 10%, the standard deviations of site-specific TRPs by about 40%, and the repeatability of daily coordinate estimates by up to 2.3 mm (50%).
first_indexed 2025-11-14T08:43:22Z
format Journal Article
id curtin-20.500.11937-35912
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:43:22Z
publishDate 2014
publisher IEEE Geoscience and Remote Sensing Society
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-359122017-09-13T15:20:56Z A realistic and easy-to-implement weighting model for GNSS phase observations Luo, X. Mayer, M. Heck, B. Awange, Joseph - stochastic model observation - weighting satellite elevation angle signal-to-noise ratio (SNR) Global Positioning System (GPS) Observation weighting is an essential component of GPS stochastic modeling and plays a key role in reliable outlier detection and parameter estimation. Nowadays, satellite elevation angle and SNR are used as quality indicators for GPS phase measurements in high-accuracy geodetic applications. In comparison with elevation-dependent models, SNR-based weighting schemes represent the reality better, but usually require greater implementation efforts. Relying upon a representative analysis of empirical SNR-based weights, this paper proposes the elevation-dependent exponential weighting function EXPZ, which benefits from realistic SNR-based weights and enables easy software implementation. To process GPS data from a regional network, this advanced weighting scheme is implemented in the Bernese GPS Software 5.0 and is compared with the conventional elevation-dependent COSZ model in terms of phase ambiguity resolution, troposphere parameter (TRP) estimation, and site coordinate determination. The results show that the proposed EXPZ model significantly attenuates the downweighting effects on low-elevation observations and improves the success rates of ambiguity resolution by about 10%, the standard deviations of site-specific TRPs by about 40%, and the repeatability of daily coordinate estimates by up to 2.3 mm (50%). 2014 Journal Article http://hdl.handle.net/20.500.11937/35912 10.1109/TGRS.2013.2294946 IEEE Geoscience and Remote Sensing Society fulltext
spellingShingle - stochastic model
observation - weighting
satellite elevation angle
signal-to-noise ratio (SNR)
Global Positioning System (GPS)
Luo, X.
Mayer, M.
Heck, B.
Awange, Joseph
A realistic and easy-to-implement weighting model for GNSS phase observations
title A realistic and easy-to-implement weighting model for GNSS phase observations
title_full A realistic and easy-to-implement weighting model for GNSS phase observations
title_fullStr A realistic and easy-to-implement weighting model for GNSS phase observations
title_full_unstemmed A realistic and easy-to-implement weighting model for GNSS phase observations
title_short A realistic and easy-to-implement weighting model for GNSS phase observations
title_sort realistic and easy-to-implement weighting model for gnss phase observations
topic - stochastic model
observation - weighting
satellite elevation angle
signal-to-noise ratio (SNR)
Global Positioning System (GPS)
url http://hdl.handle.net/20.500.11937/35912