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Projecte llegit

Títol: Characterization of Real-Time GNSS Orbit Errors from SSR-Augmented Broadcast Ephemeris

Estudiants que han llegit aquest projecte:

Director/a: SANZ SUBIRANA, JAUME

Departament: MAT

Títol: Characterization of Real-Time GNSS Orbit Errors from SSR-Augmented Broadcast Ephemeris

Data inici oferta: 30-01-2026     Data finalització oferta: 30-09-2026


Estudis d'assignació del projecte:
    DG ENG AERO/SIS TEL
Tipus: Individual
 
Lloc de realització: EETAC
 
Segon director/a (UPC): ARAGON ANGEL, MARIA ANGELES
 
Paraules clau:
GNSS, GPS, Galieo, BeiDou, Orbits, accuracy
 
Descripció del contingut i pla d'activitats:
The proliferation of high-precision real-time Global Navigation Satellite System (GNSS) applications, from autonomous navigation to precise surveying, is critically dependent on the quality of real-time satellite orbit and clock data. These products are typically generated by augmenting the standard broadcast ephemeris with Real-Time State Space Representation (SSR) corrections delivered via internet protocols. However, a comprehensive, independent characterization of the errors associated with these combined products across multiple constellations is essential for performance benchmarking and risk assessment.
This project presents a methodology and analysis for characterizing the Signal-in-Space Errors of real-time precise orbits for GPS, Galileo, and BeiDou satellites. We implement a processing pipeline that ingests live SSR correction streams and broadcast navigation messages to generate real-time satellite states. These are rigorously validated against final precise ephemeris products from the International GNSS Service (IGS), which serve as a reference truth. The analysis decomposes the total error into its constituent orbital (radial, along-track, cross-track). Key performance metrics-including accuracy (RMS), precision (STD), and clock stability-are computed statistically over an extended observation period.
The results provide a clear benchmark for the current state-of-the-art in SSR-based positioning, highlight performance differences between GNSS constellations, and offer critical data to users and service providers for optimizing real-time, high-accuracy positioning solutions.
 
Overview (resum en anglès):
The proliferation of high-precision real-time Global Navigation Satellite System (GNSS) applications, from autonomous navigation to precise surveying, is critically dependent on the quality of real-time satellite orbit data. These products are typically generated by augmenting the standard broadcast ephemeris with State Space Representation (SSR) corrections, delivered in real time. However, a comprehensive, independent characterization of the errors associated with these combined products across multiple constellations and providers is essential for performance benchmarking and risk assessment.
This project presents a methodology and analysis for characterizing the orbit errors of real-time SSR-corrected positions for GPS, Galileo, BeiDou, and GLONASS satellites, generated by four independent real-time analysis centers: WHU, CNES, HAS-JRC, and HAS-GAG. To this end, an open-source tool, Rtsatcoor, has been developed to reconstruct satellite positions from broadcast ephemeris and SSR corrections. The resulting orbits are evaluated through two complementary approaches: an internal consistency check against each provider's own precise orbit product, and an absolute accuracy assessment against final precise orbits, taken as an independent reference. The total error is decomposed into its radial, along-track, and cross-track components, and key performance metrics, including accuracy (RMS), precision (STD), and the daily rate of anomalous events, are computed statistically over an observation period spanning up to a year.
The results provide a systematic, reproducible benchmark for the current state of the art in real-time SSR-based orbit corrections across multiple constellations and independent providers. Rtsatcoor is made openly available, offering a validated tool to extend this characterization to additional providers, constellations, and time periods, and providing users and service providers with the methodology needed to assess the suitability of these correction streams for their own real-time positioning applications.

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