Establishment of Regional Tropospheric Delay Model in Australia

Ma, Yongchao; Chen, Peng; Liu, Huan; Ruan, Qingshan

doi:10.1007/978-981-13-7751-8_16

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…In addition, the University of New Brunswick (UNB) series of models (UNB1-UNB4) has been extensively used in several regions around the world. The relatively recent version UNB3m has a higher overall accuracy than the UNB3 and UNB4 models [29][30][31]. Therefore, the performance of UNB3m was also investigated using radiosonde data and compared to that of the new model.…”

Section: Assessment Of Zwd Model With Radiosondementioning

confidence: 99%

A New Method for Estimating Tropospheric Zenith Wet-Component Delay of GNSS Signals from Surface Meteorology Data

Xia

Jing-chao

et al. 2020

Remote Sensing

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A new concept is proposed for estimating the zenith wet delay (ZWD) and atmospheric weighted average temperature by inputting the temperature, total pressure, and specific humidity from surface weather data. In addition, a new ZWD integral method is described for highly accurate calculation of the ZWD from radiosonde observation. To evaluate the advantages of the new discrete integral formula, we utilized the 8-year radiosonde profiles of 85 stations in China from 2010 to 2017 to validate the accuracy of the radiosonde-derived ZWD. The results showed that the mean accuracy of the ZWD derived from radiosonde data was 4.28 mm. Next, the new ZWD model was assessed using two sets of reference values derived from radiosonde data and GNSS precise point positioning in China. The results confirm that the new development improved the accuracy of the estimation of the tropospheric wet delay from the surface meteorological data. The performance of this new model can be seen as an important step toward accurately correcting the tropospheric delay in Global Navigation Satellite System (GNSS) real-time navigation and positioning. It can also be used in GNSS meteorology for weather forecasting and climate research.

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Section: Assessment Of Zwd Model With Radiosondementioning

confidence: 99%

A New Method for Estimating Tropospheric Zenith Wet-Component Delay of GNSS Signals from Surface Meteorology Data

Xia

Jing-chao

et al. 2020

Remote Sensing

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“…Nonetheless, each atmospheric layer has a different impact on the GNSS signals, of which the ionospheric delay can to a large extent be removed by an ionosphere-free linear combination of dual or multi-frequency GNSS observables owing to its dispersive nature (Wang and Li, 2016). This leaves tropospheric delay as the major error source in GNSS applications (Ma et al, 2019). The impact of tropospheric delay ranges from about 2.0 to 2.6m in the zenith direction to about 20 to 28m near the horizon and at lower elevation angles (Sanlioglu and Zeybek, 2012).…”

Section: Introductionmentioning

confidence: 99%

Comparative evaluation and analysis of different tropospheric delay models in Ghana

Osah¹,

Acheampong²,

Dadzie³

et al. 2022

SA J of Geomatics

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Tropospheric delay prediction models have become increasingly important in Global Navigation Satellite System (GNSS) as they play a critical role in GNSS positioning applications. Due to the different atmospheric conditions over the earth regions, tropospheric effect on GNSS signals also differs, influencing the performance of these prediction models. Thus, the choice of a particular prediction model can significantly degrade the positioning accuracy especially when the model does not suit the user’s environs. Therefore, a performance assessment of existing prediction models in various regions for a suitable one is very imperative. This paper evaluates and analyses seven commonly used tropospheric delay models in Ghana in terms of performances in Zenith Tropospheric Delay (ZTD) estimation and baseline positional accuracies using data from six selected Continuously Operating Reference Stations (CORS). The 1˚x1˚ gridded Vienna Mapping Functions 3 (VMF3) ZTD product and coordinates solutions from the CSRS-PPP positioning service were respectively used as references. The results show that the Black model performed better in estimating the ZTD, followed by Askne and Nordius model. The Saastamoinen, Marini and Murray, Niell, Goads and Goodman and Hopfield models respectively performed poorly. However, the result of the baseline solutions did not show much variation in the coordinate difference provided by the use of the prediction models, nonetheless, the Black and Askne and Nordius models continue to dominate the other models. Of all the models evaluated, either Black or Askne and Nordius model is recommended for use to mitigate the ZTD in the study area, however, the choice of the Black model will be more desirable.

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A high-precision ZTD interpolation method considering large area and height differences

Zhao,

Wang,

et al. 2023

GPS Solut

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Establishment of Regional Tropospheric Delay Model in Australia

Cited by 3 publications

References 8 publications

A New Method for Estimating Tropospheric Zenith Wet-Component Delay of GNSS Signals from Surface Meteorology Data

A New Method for Estimating Tropospheric Zenith Wet-Component Delay of GNSS Signals from Surface Meteorology Data

Comparative evaluation and analysis of different tropospheric delay models in Ghana

A high-precision ZTD interpolation method considering large area and height differences

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