Reprocessing Multiple GNSS Constellations and a Global Station Network from 1994 to 2020 with the Raw Observation Approach

Sebastian Strasser

doi:10.3217/978-3-85125-885-1

Reprocessing Multiple GNSS Constellations and a Global Station Network from 1994 to 2020 with the Raw Observation Approach

Sebastian Strasser

Institut für Geodäsie (5220)

Publikation: Studienabschlussarbeit › Dissertation

Abstract

Ein genauer und stabiler globaler geodätischer Referenzrahmen, wie der Internationale Terrestrische Referenzrahmen (ITRF), ist von grundlegender Bedeutung für die Quantifizierung geophysikalischer Veränderungen im Erdsystem. Globale Satellitennavigationssysteme (GNSS) sind eine der vier weltraumgeodätischen Techniken, die zum ITRF beitragen. Für den ITRF2020 führte der Internationale GNSS Service (IGS) seine dritte Reprozessierungskampagne (repro3) durch, welche die Jahre 1994 bis 2020 umfasst. In dieser Arbeit wird die Methodik hinter dem Beitrag der Technischen Universität Graz (TU Graz) zu repro3 beschrieben. Die Reprozessierung umfasste die Satellitenkonstellationen GPS, GLONASS und Galileo sowie 1182 Bodenstationen. Pro Tag wurden mehr als 800 Stationen verarbeitet, was zu Gleichungssystemen mit hunderten Millionen Beobachtungen und Millionen Parametern führte. Es wird erläutert, wie der Rohbeobachtungsansatz implementiert wurde, um eine Prozessierung dieses Ausmaßes zu ermöglichen. Alle verwendeten Parametrisierungen, Modelle und Korrekturen werden detailliert. Die Evaluierung der resultierenden GNSS-Produkte zeigt deren sehr hohe Qualität. Dies wird dadurch bestätigt, dass der repro3-Beitrag der TU Graz das höchste Gewicht in der IGS-Referenzrahmenkombination erhielt

Originalsprache	englisch
Qualifikation	Doktor der Technik
Gradverleihende Hochschule	Technische Universität Graz (90000)
Betreuer/-in / Berater/-in	Mayer-Gürr, Torsten, Betreuer
Erscheinungsort	Graz
Herausgeber (Verlag)	Verlag der Technischen Universität Graz
ISBN's (ebook)	978-3-85125-885-1
DOIs	https://doi.org/10.3217/978-3-85125-885-1
Publikationsstatus	Veröffentlicht - 29 Apr. 2022

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10.3217/978-3-85125-885-1Lizenz: CC BY 4.0

Strasser_2022_Doctoral_ThesisEndgültige, publizierte Fassung, 5,8 MBLizenz: CC BY 4.0

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@phdthesis{11add8069ac2429a8cd622657bb179a3,

title = "Reprocessing Multiple GNSS Constellations and a Global Station Network from 1994 to 2020 with the Raw Observation Approach",

abstract = "An accurate and stable global geodetic reference frame, such as the International Terrestrial Reference Frame (ITRF), is fundamental for quantifying geophysical changes in the Earth system. Global navigation satellite systems (GNSS) are one of the four space-geodetic techniques contributing to the construction of the ITRF. In support of the upcoming ITRF2020 release, the International GNSS Service (IGS) conducted its third reprocessing campaign (repro3), covering the years 1994 to 2020. Graz University of Technology (TUG) participated for the first time as an analysis center in such a reprocessing.This thesis thoroughly describes the methodologies behind TUG's repro3 contribution. The reprocessing included the three satellite constellations GPS, GLONASS, and Galileo as well as a total of 1182 ground stations. In the latter third of the time series, more than 800 stations were processed per day, resulting in equation systems with hundreds of millions of observations and millions of parameters. The thesis delineates how the raw observation approach was implemented to facilitate a GNSS processing of this scale. This includes methods and strategies developed to handle the extraordinary computational challenges of this reprocessing. All applied parametrizations, models, and corrections are elaborated in detail. For example, generalized methods for the parametrization of code and phase biases in a multi-signal environment are presented.The evaluation of the resulting GNSS products showed that they are of very high quality. TUG{\textquoteright}s repro3 contribution gained the highest weight on average in the IGS reference frame combination. The consistency of the obtained satellite orbits is also very high, which was confirmed by preliminary orbit combination results. This means that the methods delineated in this thesis lead to GNSS products that are very competitive with those of other IGS analysis centers. Therefore, the targets of reaching this quality level and providing a valuable contribution to ITRF2020 were successfully achieved.",

keywords = "Multi-GNSS, GPS, GLONASS, Galileo, IGS, Repro3, Reference Frame, ITRF, TUG, Graz University of Technology, Orbit Determination, Ambiguity Resolution, Signal Biases, Satellite Attitude",

author = "Sebastian Strasser",

year = "2022",

month = apr,

day = "29",

doi = "10.3217/978-3-85125-885-1",

language = "English",

series = "Monographic Series TU Graz – Geodesy",

publisher = "Verlag der Technischen Universit{\"a}t Graz",

school = "Graz University of Technology (90000)",

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TY - BOOK

T1 - Reprocessing Multiple GNSS Constellations and a Global Station Network from 1994 to 2020 with the Raw Observation Approach

AU - Strasser, Sebastian

PY - 2022/4/29

Y1 - 2022/4/29

N2 - An accurate and stable global geodetic reference frame, such as the International Terrestrial Reference Frame (ITRF), is fundamental for quantifying geophysical changes in the Earth system. Global navigation satellite systems (GNSS) are one of the four space-geodetic techniques contributing to the construction of the ITRF. In support of the upcoming ITRF2020 release, the International GNSS Service (IGS) conducted its third reprocessing campaign (repro3), covering the years 1994 to 2020. Graz University of Technology (TUG) participated for the first time as an analysis center in such a reprocessing.This thesis thoroughly describes the methodologies behind TUG's repro3 contribution. The reprocessing included the three satellite constellations GPS, GLONASS, and Galileo as well as a total of 1182 ground stations. In the latter third of the time series, more than 800 stations were processed per day, resulting in equation systems with hundreds of millions of observations and millions of parameters. The thesis delineates how the raw observation approach was implemented to facilitate a GNSS processing of this scale. This includes methods and strategies developed to handle the extraordinary computational challenges of this reprocessing. All applied parametrizations, models, and corrections are elaborated in detail. For example, generalized methods for the parametrization of code and phase biases in a multi-signal environment are presented.The evaluation of the resulting GNSS products showed that they are of very high quality. TUG’s repro3 contribution gained the highest weight on average in the IGS reference frame combination. The consistency of the obtained satellite orbits is also very high, which was confirmed by preliminary orbit combination results. This means that the methods delineated in this thesis lead to GNSS products that are very competitive with those of other IGS analysis centers. Therefore, the targets of reaching this quality level and providing a valuable contribution to ITRF2020 were successfully achieved.

AB - An accurate and stable global geodetic reference frame, such as the International Terrestrial Reference Frame (ITRF), is fundamental for quantifying geophysical changes in the Earth system. Global navigation satellite systems (GNSS) are one of the four space-geodetic techniques contributing to the construction of the ITRF. In support of the upcoming ITRF2020 release, the International GNSS Service (IGS) conducted its third reprocessing campaign (repro3), covering the years 1994 to 2020. Graz University of Technology (TUG) participated for the first time as an analysis center in such a reprocessing.This thesis thoroughly describes the methodologies behind TUG's repro3 contribution. The reprocessing included the three satellite constellations GPS, GLONASS, and Galileo as well as a total of 1182 ground stations. In the latter third of the time series, more than 800 stations were processed per day, resulting in equation systems with hundreds of millions of observations and millions of parameters. The thesis delineates how the raw observation approach was implemented to facilitate a GNSS processing of this scale. This includes methods and strategies developed to handle the extraordinary computational challenges of this reprocessing. All applied parametrizations, models, and corrections are elaborated in detail. For example, generalized methods for the parametrization of code and phase biases in a multi-signal environment are presented.The evaluation of the resulting GNSS products showed that they are of very high quality. TUG’s repro3 contribution gained the highest weight on average in the IGS reference frame combination. The consistency of the obtained satellite orbits is also very high, which was confirmed by preliminary orbit combination results. This means that the methods delineated in this thesis lead to GNSS products that are very competitive with those of other IGS analysis centers. Therefore, the targets of reaching this quality level and providing a valuable contribution to ITRF2020 were successfully achieved.

KW - Multi-GNSS

KW - GPS

KW - GLONASS

KW - Galileo

KW - IGS

KW - Repro3

KW - Reference Frame

KW - ITRF

KW - TUG

KW - Graz University of Technology

KW - Orbit Determination

KW - Ambiguity Resolution

KW - Signal Biases

KW - Satellite Attitude

U2 - 10.3217/978-3-85125-885-1

DO - 10.3217/978-3-85125-885-1

M3 - Doctoral Thesis

T3 - Monographic Series TU Graz – Geodesy

PB - Verlag der Technischen Universität Graz

CY - Graz

ER -

Reprocessing Multiple GNSS Constellations and a Global Station Network from 1994 to 2020 with the Raw Observation Approach

Abstract

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