Results 1 to 10 of about 343 (133)

A Regional Zenith Tropospheric Delay (ZTD) Model Based on GPT3 and ANN [PDF]

open access: yesRemote Sensing, 2021
The delays of radio signals transmitted by global navigation satellite system (GNSS) satellites and induced by neutral atmosphere, which are usually represented by zenith tropospheric delay (ZTD), are required as critical information both for GNSS ...
Fei Yang   +4 more
doaj   +4 more sources

Comprehensive Analysis of the Global Zenith Tropospheric Delay Real-Time Correction Model Based GPT3

open access: yesAtmosphere, 2023
To obtain a higher accuracy for the real-time Zenith Tropospheric Delay (ZTD), a refined tropospheric delay correction model was constructed by combining the tropospheric delay correction model based on meteorological parameters and the GPT3 model.
Jian Chen   +4 more
doaj   +4 more sources

Assessment of Empirical Troposphere Model GPT3 Based on NGL’s Global Troposphere Products [PDF]

open access: yesSensors, 2020
Tropospheric delay is one of the major error sources in GNSS (Global Navigation Satellite Systems) positioning. Over the years, many approaches have been devised which aim at accurately modeling tropospheric delays, so-called troposphere models.
Junsheng Ding, Junping Chen
doaj   +6 more sources

A Calibrated GPT3 (CGPT3) Model for the Site-Specific Zenith Hydrostatic Delay Estimation in the Chinese Mainland and Its Surrounding Areas

open access: yesRemote Sensing, 2022
The prior zenith hydrostatic delay (ZHD) is an essential parameter for the Global Navigation Satellite System (GNSS) and very long baseline interferometry (VLBI) high-precision data processing. Meanwhile, the precise ZHD facilitates the separation of the
Junyu Li   +5 more
doaj   +5 more sources

A Refined Zenith Tropospheric Delay Model Based on a Generalized Regression Neural Network and the GPT3 Model in Europe

open access: yesAtmosphere, 2023
An accurate model of the Zenith Tropospheric Delay (ZTD) plays a crucial role in Global Navigation Satellite System (GNSS) precise positioning, water vapor retrieval, and meteorological research. Current empirical models (such as the GPT3 model) can only
Min Wei   +4 more
doaj   +4 more sources

The New Improved ZHD and Weighted Mean Temperature Models Based on GNSS and Radiosonde Data Using GPT3 and Fourier Function

open access: yesAtmosphere, 2022
Compared to the zenith hydrostatic delay (ZHD) obtained from the Saastamonien model based on in-situ measured meteorological (IMM) data and radiosonde-derived weighted mean temperature (Tm), the ZHD and Tm deviations of the GPT3 model have shown obvious ...
Li Li   +5 more
doaj   +4 more sources

Forecasting GNSS Zenith Troposphere Delay by Improving GPT3 Model with Machine Learning in Antarctica [PDF]

open access: yesAtmosphere, 2022
Antarctica has a significant impact on global climate change. However, to draw climate change scenarios, there is a need for meteorological data, such as water vapor content, which is scarce in Antarctica.
Song Li   +4 more
doaj   +4 more sources

A zenith wet delay improved model in China based on GPT3 and random forest

open access: yesGeodesy and Geodynamics
Zenith wet delay (ZWD) is a key parameter for the precise positioning of global navigation satellite systems (GNSS) and occupies a central role in meteorological research.
Shaoni Chen   +5 more
doaj   +4 more sources

Refining relative tropospheric delay modeling of GPT3 for large-height-difference RTK positioning

open access: yesFrontiers in Astronomy and Space Sciences
Real-Time Kinematic (RTK) positioning technique, with centimeter-level accuracy, is widely used in landslide deformation and building structural health monitoring. However, in large-height-difference scenarios where the height difference between the base
Peida Wu   +8 more
doaj   +2 more sources

TransXLT: A novel ZTD prediction method with SASR-based data reconstruction [PDF]

open access: yesiScience
Summary: Traditional Zenith Tropospheric Delay (ZTD) models often face difficulties in maintaining prediction accuracy under complex meteorological conditions and data loss.
Shicheng Xie   +7 more
doaj   +2 more sources

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