On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Organisationseinheiten

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksInternational Association of Geodesy Symposia
Herausgeber/-innenJeffrey T. Freymueller, Laura Sánchez
ErscheinungsortBerlin
Herausgeber (Verlag)Springer Nature
Seiten345-357
Seitenumfang13
ISBN (Print)9783031295065
PublikationsstatusVeröffentlicht - 28 Juli 2022

Publikationsreihe

NameInternational Association of Geodesy Symposia
Band154
ISSN (Print)0939-9585
ISSN (elektronisch)2197-9359

Abstract

For highly precise and accurate positioning and navigation with Global Navigation Satellite Systems (GNSS), it is mandatory to take phase center corrections (PCC) into account. These corrections are provided by different calibration facilities and methods. Currently, discussions in the framework of the International GNSS Service (IGS) antenna working group (AWG) are ongoing on how to accept new calibration facilities as an official IGS calibration facility. In this paper, different image similarity measures and their potential for comparing PCC are presented. Currently used comparison strategies are discussed and their performance is illustrated with several geodetic antennas. We show that correlation coefficients are an appropriate measure to compare different sets of PCC since they perform independently of a constant part within the patterns. However, feature detection algorithms like the Speeded-Up Robust Features (SURF) mostly do not find distinctive structures within the PCC differences due to the smooth character of PCC. Therefore, they are inapplicable for comparing PCC. Singular Value Decomposition (SVD) of PCC differences (ΔPCC) can be used to analyse which structures ΔPCC are composed of. We show that characteristic structures can be found within ΔPCC. Therefore, the SVD is a promising tool to analyse the impact of PCC differences in the coordinate domain.

ASJC Scopus Sachgebiete

Fachgebiet (basierend auf ÖFOS 2012)

  • TECHNISCHE WISSENSCHAFTEN
  • Elektrotechnik, Elektronik, Informationstechnik
  • Elektrotechnik, Elektronik, Informationstechnik
  • Mikrowellentechnik
  • TECHNISCHE WISSENSCHAFTEN
  • Umweltingenieurwesen, Angewandte Geowissenschaften
  • Geodäsie, Vermessungswesen
  • Satellitengeodäsie
  • TECHNISCHE WISSENSCHAFTEN
  • Umweltingenieurwesen, Angewandte Geowissenschaften
  • Geodäsie, Vermessungswesen
  • Satellitengestützte Koordinatenmessung

Zitieren

On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections. / Kröger, Johannes; Kersten, Tobias; Breva, Yannick et al.
International Association of Geodesy Symposia. Hrsg. / Jeffrey T. Freymueller; Laura Sánchez. Berlin: Springer Nature, 2022. S. 345-357 (International Association of Geodesy Symposia; Band 154).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Kröger, J, Kersten, T, Breva, Y & Schön, S 2022, On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections. in JT Freymueller & L Sánchez (Hrsg.), International Association of Geodesy Symposia. International Association of Geodesy Symposia, Bd. 154, Springer Nature, Berlin, S. 345-357. https://doi.org/10.1007/1345_2022_146
Kröger, J., Kersten, T., Breva, Y., & Schön, S. (2022). On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections. In J. T. Freymueller, & L. Sánchez (Hrsg.), International Association of Geodesy Symposia (S. 345-357). (International Association of Geodesy Symposia; Band 154). Springer Nature. https://doi.org/10.1007/1345_2022_146
Kröger J, Kersten T, Breva Y, Schön S. On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections. in Freymueller JT, Sánchez L, Hrsg., International Association of Geodesy Symposia. Berlin: Springer Nature. 2022. S. 345-357. (International Association of Geodesy Symposia). doi: 10.1007/1345_2022_146
Kröger, Johannes ; Kersten, Tobias ; Breva, Yannick et al. / On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections. International Association of Geodesy Symposia. Hrsg. / Jeffrey T. Freymueller ; Laura Sánchez. Berlin : Springer Nature, 2022. S. 345-357 (International Association of Geodesy Symposia).
Download
@inproceedings{9ee47ade15a24a4c8846db056d9aad0a,
title = "On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections",
abstract = "For highly precise and accurate positioning and navigation with Global Navigation Satellite Systems (GNSS), it is mandatory to take phase center corrections (PCC) into account. These corrections are provided by different calibration facilities and methods. Currently, discussions in the framework of the International GNSS Service (IGS) antenna working group (AWG) are ongoing on how to accept new calibration facilities as an official IGS calibration facility. In this paper, different image similarity measures and their potential for comparing PCC are presented. Currently used comparison strategies are discussed and their performance is illustrated with several geodetic antennas. We show that correlation coefficients are an appropriate measure to compare different sets of PCC since they perform independently of a constant part within the patterns. However, feature detection algorithms like the Speeded-Up Robust Features (SURF) mostly do not find distinctive structures within the PCC differences due to the smooth character of PCC. Therefore, they are inapplicable for comparing PCC. Singular Value Decomposition (SVD) of PCC differences (ΔPCC) can be used to analyse which structures ΔPCC are composed of. We show that characteristic structures can be found within ΔPCC. Therefore, the SVD is a promising tool to analyse the impact of PCC differences in the coordinate domain.",
keywords = "phase center corrections (PCC), Multi-GNSS processing, Image similarity metrics, Singular value decomposition, Phase center corrections",
author = "Johannes Kr{\"o}ger and Tobias Kersten and Yannick Breva and Steffen Sch{\"o}n",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
month = jul,
day = "28",
doi = "10.1007/1345_2022_146",
language = "English",
isbn = "9783031295065",
series = "International Association of Geodesy Symposia",
publisher = "Springer Nature",
pages = "345--357",
editor = "Freymueller, {Jeffrey T.} and Laura S{\'a}nchez",
booktitle = "International Association of Geodesy Symposia",
address = "United States",

}

Download

TY - GEN

T1 - On the Potential of Image Similarity Metrics for Comparing Phase Center Corrections

AU - Kröger, Johannes

AU - Kersten, Tobias

AU - Breva, Yannick

AU - Schön, Steffen

N1 - Publisher Copyright: © 2022, The Author(s).

PY - 2022/7/28

Y1 - 2022/7/28

N2 - For highly precise and accurate positioning and navigation with Global Navigation Satellite Systems (GNSS), it is mandatory to take phase center corrections (PCC) into account. These corrections are provided by different calibration facilities and methods. Currently, discussions in the framework of the International GNSS Service (IGS) antenna working group (AWG) are ongoing on how to accept new calibration facilities as an official IGS calibration facility. In this paper, different image similarity measures and their potential for comparing PCC are presented. Currently used comparison strategies are discussed and their performance is illustrated with several geodetic antennas. We show that correlation coefficients are an appropriate measure to compare different sets of PCC since they perform independently of a constant part within the patterns. However, feature detection algorithms like the Speeded-Up Robust Features (SURF) mostly do not find distinctive structures within the PCC differences due to the smooth character of PCC. Therefore, they are inapplicable for comparing PCC. Singular Value Decomposition (SVD) of PCC differences (ΔPCC) can be used to analyse which structures ΔPCC are composed of. We show that characteristic structures can be found within ΔPCC. Therefore, the SVD is a promising tool to analyse the impact of PCC differences in the coordinate domain.

AB - For highly precise and accurate positioning and navigation with Global Navigation Satellite Systems (GNSS), it is mandatory to take phase center corrections (PCC) into account. These corrections are provided by different calibration facilities and methods. Currently, discussions in the framework of the International GNSS Service (IGS) antenna working group (AWG) are ongoing on how to accept new calibration facilities as an official IGS calibration facility. In this paper, different image similarity measures and their potential for comparing PCC are presented. Currently used comparison strategies are discussed and their performance is illustrated with several geodetic antennas. We show that correlation coefficients are an appropriate measure to compare different sets of PCC since they perform independently of a constant part within the patterns. However, feature detection algorithms like the Speeded-Up Robust Features (SURF) mostly do not find distinctive structures within the PCC differences due to the smooth character of PCC. Therefore, they are inapplicable for comparing PCC. Singular Value Decomposition (SVD) of PCC differences (ΔPCC) can be used to analyse which structures ΔPCC are composed of. We show that characteristic structures can be found within ΔPCC. Therefore, the SVD is a promising tool to analyse the impact of PCC differences in the coordinate domain.

KW - phase center corrections (PCC)

KW - Multi-GNSS processing

KW - Image similarity metrics

KW - Singular value decomposition

KW - Phase center corrections

UR - http://www.scopus.com/inward/record.url?scp=85172669294&partnerID=8YFLogxK

U2 - 10.1007/1345_2022_146

DO - 10.1007/1345_2022_146

M3 - Conference contribution

SN - 9783031295065

T3 - International Association of Geodesy Symposia

SP - 345

EP - 357

BT - International Association of Geodesy Symposia

A2 - Freymueller, Jeffrey T.

A2 - Sánchez, Laura

PB - Springer Nature

CY - Berlin

ER -

Von denselben Autoren