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Multi-GNSS Processing Software

Research question: How can we incorporate signals from all available GNSS constellations in order to get a more accurate position?

As satellite navigation systems expand and proliferate, NOAA’s National Geodetic Survey (NGS) software and methods evolve to benefit from these changes, increasing the accuracy and accessibility of geospatial data. As of 2024, four Global Navigation Satellite Systems (GNSSs) are fully operational: the United States' Global Positioning System (G P S), Russia's Global Navigation Satellite System (GLONASS), China's BeiDou Navigation Satellite System (BDS) , and the European Union's Galileo. All four GNSS constellations share the same fundamental principles for determining positioning:

  • Each GNSS operates through a constellation of satellites orbiting the Earth in specific orbits to ensure global coverage.
  • GNSS satellites continuously broadcast signals containing information about their position and precise time.
  • Commercial receiver hardware are able to collect GNSS signals and are able to determine the receiver’s position in space (e.g., latitude, longitude, and height).
  • Accuracy of determining positioning, navigation, and timing applications depends on the ability to account for the instrumental and environmental factors that are used for GNSS operation, such as GNSS signal propagation delays through the Earth's atmosphere (ionosphere and troposphere), satellite clock errors, and other error corrections.

With multiple GNSS constellations, most of which broadcast on three or more frequencies, it is possible to calculate position more rapidly and improve positioning accuracy, especially in areas with limited skyview. As such, NGS has been upgrading and enhancing its legacy orbit/baseline estimation software known as Program for Adjustment of GPS Ephemerides (PAGES) to allow processing of any GNSS constellation for geodetic applications. The multi-constellations software upgrade to PAGES is called M-PAGES and it uses a single-difference phase approach. The M-PAGES software is capable of processing data from all available GNSS with two or more frequencies that allows the flexibility to add existing and future GNSS constellations. Furthermore, M-PAGES accepts data in all Receiver INdependent EXchange (RINEX) formats.

The M-PAGES has been developed internally in NOAA and serves as an engine software for many applications supporting the new national geospatial infrastructure, known as the National Spatial Reference System. For example, M-PAGES is the key engine in NOAA’s Online Positioning User Service Online Positioning User Service (OPUS) that enables end users, such as land surveyors, to calculate precise and accurate positions using a network of permanent stations (a.k.a., Continuously Operating Reference Stations, CORS). M-PAGES software will also be used to determine precise GNSS satellite orbits for the NGS Analysis Center daily operations. The research and development for M-PAGES goes beyond adding more satellite constellations and signal processing. M-PAGES research also includes new geodetic approaches, such as use of the baseline GNSS vectors in survey network adjustments and minimizes the dependence of the software on external precise GNSS products.

Image of OPUS: Online Positioning Service interface

Peer Review Publications and Conference Presentations

Stressler, B., A. Bilich, C. Ogaja, J. and Heck. 2021. “Multi-GNSS single-difference baseline processing at NGS with newly developed M-PAGES software,.” EGU General Assembly, online, 19–30 Apr 2021, EGU21-5556, https://doi.org/10.5194/egusphere-egu21-5556.

Bilich, A., A. Slater, and K. Larson. 2011. Snow Depth with GPS: Case Study from Minnesota 2010-2011. Presentation at 2011 AGU Fall Meeting. https://geodesy.noaa.gov/web/science_edu/presentations_archive/files/agu11poster_mnsnowv2.pdf

Ogaja, C.A. 2022. Introduction to GNSS Geodesy: Foundations of Precise Positioning Using Global Navigation Satellite Systems. Switzerland AG: Springer, Cham. https://doi.org/10.1007/978-3-030-91821-7.

Teunissen, P.J.G., and O. Montenbruck. 2017. Springer Handbook of Global Navigation Satellite Systems. Switzerland AG: Springer Cham. https://doi.org/10.1007/978-3-319-42928-1.

Ogaja, C., A. Bilich, and R. Bennett. 2024. "Optimal cycle slip detection algorithm for GPS/GNSS preprocessing using three linear combinations of moderate to low noise data." J. Surv. Eng. https://doi.org/10.1061/JSUED2.SUENG-1525