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

authored by: Johannes Kröger, Tobias Kersten, Yannick Breva, Steffen Schön
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.
Organisation(s): Institute of Geodesy
Type: Conference contribution
Pages: 345-357
No. of pages: 13
Publication date: 28.07.2022
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Applied Mathematics, Electrical and Electronic Engineering, Computers in Earth Sciences, Geophysics
Research Area (based on ÖFOS 2012): Microwave engineering, Satellite geodesy, Satellite-based coordinate measuring
Electronic version(s): https://doi.org/10.1007/1345_2022_146 (Access: Open)
: Details in the research portal "Research@Leibniz University"

BibTeX

@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",
}