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GSeisRT: regional GNSS point positioning for wide-area seismic monitoring in real time

Urheber*innen

Geng,  Jianghui
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Xin,  Shaoming
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Zhang,  Kunlun
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Zitation

Geng, J., Xin, S., Zhang, K. (2023): GSeisRT: regional GNSS point positioning for wide-area seismic monitoring in real time, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-5024


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021422
Zusammenfassung
GSeisRT software developed by Wuhan University is dedicated to real-time GNSS data processing, and it is free and open for the science community under mutual agreement. GSeisRT consists of a server end and a client end. GSeisRT server can use a regional GNSS network to estimate satellite clocks and phase biases independently or access IGS (International GNSS Service) real-time clock and orbit products to estimate satellite phase biases, which is more flexible and compatible with different data scenarios. Then GSeisRT client can realize multi-GNSS (GPS/GLONASS/GALILEO/QZSS/BeiDou) precise point positioning with ambiguity resolution (PPP-AR) and achieve centimeter-level to sub-centimeter-level precision in real time based on the products of GSeisRT server or IGS real-time service. The acquisition of real-time position can be applied to scenarios such as earthquake displacement monitoring, which is necessary and socially significant. In addition, GSeisRT will provide a lite version of the client with a user interface that can estimate and display the ionospheric delay of multi-GNSS satellites in real time. Considering user privacy and data security, GSeisRT could not only support the processing of public data streams but also be deployed in a private operating environment to process proprietary data streams, then users' data security and autonomy can be guaranteed.