Analyzing Rinex Data Files Using the Python Programming Language

Author:

Bălă Alina Corina1,Drăgulescu B.C.2,Brebu Floarea-Maria1

Affiliation:

1. Politehnica University Timisoara, Faculty of Civil Engineering , Department of Overland Communication Ways, Foundations and Cadastral Survey , 2 Traian Lalescu Street , Romania

2. Politehnica University Timisoara, Faculty of Electronics, Telecommunications and Information Technologies , Communications Department , 2 Bd. Vasile Pârvan , Romania

Abstract

Abstract The techniques and tools developed for geodetic determinations have made it possible, over the past half century, to carry out measurements using global navigation satellite systems. As the accuracy and precision of positioning solutions, such as Fast Static and RTK, improve through technological advances, more applications will become available that can provide users with positioning information over time, autonomously verify the integrity of transmitted data, and ensure sufficient accuracy for their intended purposes. In our study for the interpretation, analysis, and visualization of raw and/or processed RINEX GNSS data recorded over time at a geodetic point using the information available from the Fast Static technique, we used the GeoRinex library from the Python programming language. This library converts data to xarray.data set, for easy use in processing parameter sets, from Rinex files: of ROMPOS reference stations and of the new B10 point resulting from measurements using the Fast Static technique: pseudorange (C1, C2, P1, P2....), carrier phase (L1, L2,…), doppler (D1, D2....) and signal strength (S1, S2....). All this information will help us to analyse and interpret the degradation of the parameters associated with Rinex version 2.11 epoch positioning files 12.02.2023, time interval 12:00-14:00 (fast static) and to understand their accuracy and behavior in different environments. Based on this study, our aim was to evaluate the error in determining the positioning accuracy of the B10 point located in a crowded and heavily trafficked area, which allows sufficient coverage of the GNSS satellites.

Publisher

Walter de Gruyter GmbH

Reference15 articles.

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2. Gałdyn, Filip, Radosław Zajdel, and Krzysztof Sośnica. 2023. “RINEXAV: GNSS Global Network Selection Open-Source Software Based on Qualitative Analysis of RINEX Files.” SoftwareX 22 (May): 101372. https://doi.org/10.1016/j.softx.2023.101372.

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5. Li, Xianjie, Jean-Pierre Barriot, Yidong Lou, Weixing Zhang, Pengbo Li, and Chuang Shi. 2023. “Towards Millimeter-Level Accuracy in GNSS-Based Space Geodesy: A Review of Error Budget for GNSS Precise Point Positioning.” Surveys in Geophysics 44 (6): 1691–1780. https://doi.org/10.1007/s10712-023-09785-w.

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