Advancing multi-GNSS orbit combination in the variance component estimation framework
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00025615%3A_____%2F25%3AN0000015" target="_blank" >RIV/00025615:_____/25:N0000015 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s00190-025-02005-w" target="_blank" >https://link.springer.com/article/10.1007/s00190-025-02005-w</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00190-025-02005-w" target="_blank" >10.1007/s00190-025-02005-w</a>
Alternative languages
Result language
angličtina
Original language name
Advancing multi-GNSS orbit combination in the variance component estimation framework
Original language description
The International GNSS Service (IGS) requires advanced multi-GNSS orbit combination strategies to replace current GPS/GLONASS-focused operations with consistent products covering GPS, GLONASS, Galileo, and BDS. We developed an enhanced orbit combination methodology using a modified Förstner Variance Component Estimation (VCE) scheme that optimizes weighting strategies through data clustering approaches, including individual satellite weighting, satellite-type grouping, and machine-learning-generated clusters. Our novel approach incorporates a priori knowledge from Satellite Laser Ranging (SLR) orbit validations and sequential weight information from previous combinations to refine Analysis Center (AC) weights. Sequential weight estimation significantly reduces day boundary orbit misclosures and stabilizes temporal AC weight variability. The combined solutions demonstrate exceptional inter-consistency with RMS values below 3–5 mm for GPS and Galileo, while GLONASS and BDS show higher variability (10–15 mm), highlighting the importance of satellite grouping strategies. Intermediate grouping approaches based on IGS metadata or hierarchical clustering provide optimal balance between constellation-level oversimplification and satellite-specific day-to-day variability. SLR-based knowledge incorporation offers targeted improvements, particularly for challenging high and low β angle conditions, demonstrating the effectiveness of external validation in multi-GNSS orbit combination.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10511 - Environmental sciences (social aspects to be 5.7)
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Geodesy
ISSN
0949-7714
e-ISSN
1432-1394
Volume of the periodical
99
Issue of the periodical within the volume
11
Country of publishing house
DE - GERMANY
Number of pages
32
Pages from-to
—
UT code for WoS article
001605140400001
EID of the result in the Scopus database
2-s2.0-105020445089