Optimum stochastic modeling for GNSS tropospheric delay estimation in real-time
PBN-AR
Instytucja
Wydział Inżynierii Kształtowania Środowiska i Geodezji (Uniwersytet Przyrodniczy we Wrocławiu)
Informacje podstawowe
Główny język publikacji
angielski
Czasopismo
GPS SOLUTIONS (35pkt w roku publikacji)
ISSN
1080-5370
EISSN
1521-1886
Wydawca
SPRINGER HEIDELBERG
DOI
URL
Rok publikacji
2017
Numer zeszytu
3
Strony od-do
1069–1081
Numer tomu
21
Identyfikator DOI
Liczba arkuszy
Autorzy
Pozostali autorzy
+ 1
Słowa kluczowe
angielski
GNSS meteorology
Troposphere
Real-time
PPP
NWP
Streszczenia
Język
angielski
Treść
In GNSS data processing, the station height, receiver clock and tropospheric delay (ZTD) are highly correlated to each other. Although the zenith hydrostatic delay of the troposphere can be provided with sufficient accuracy, zenith wet delay (ZWD) has to be estimated, which is usually done in a random walk process. Since ZWD temporal variation depends on the water vapor content in the atmosphere, it seems to be reasonable that ZWD constraints in GNSS processing should be geographically and/or time dependent. We propose to take benefit from numerical weather prediction models to define optimum random walk process noise. In the first approach, we used archived VMF1-G data to calculate a grid of yearly and monthly means of the difference of ZWD between two consecutive epochs divided by the root square of the time lapsed, which can be considered as a random walk process noise. Alternatively, we used the Global Forecast System model from National Centres for Environmental Prediction to calculate random walk process noise dynamically in real-time. We performed two representative experimental campaigns with 20 globally distributed International GNSS Service (IGS) stations and compared real-time ZTD estimates with the official ZTD product from the IGS. With both our approaches, we obtained an improvement of up to 10% in accuracy of the ZTD estimates compared to any uniformly fixed random walk process noise applied for all stations.
Inne
System-identifier
PX-5950b8fbd5de96d84b4ed6d9
CrossrefMetadata from Crossref logo
Cytowania
Liczba prac cytujących tę pracę
Brak danych
Referencje
Liczba prac cytowanych przez tę pracę
Brak danych