Analyzing the Tropospheric Delay Estimates on Global Navigation Satellite Systems (GNSS) with Precise Point Positioning (PPP) Services using the goGPS software

https://doi.org/10.22146/jgise.56071

Syachrul Arief(1*), Andrea Gatti(2)

(1) Geospatial Information Agency Indonesia (BIG)
(2) Geomatics Research and Development s.r.l. - Lomazzo, Italy
(*) Corresponding Author

Abstract


The tropospheric delay is an essential source of error for positioning using the Global Navigation Satellite System (GNSS). Scientific applications of GNSS positioning such as the study of earth crust deformation and earthquake prediction require high accuracy in positioning, an analysis of tropospheric delay calculations is needed to improve the accuracy of GNSS positioning. One part of the tropospheric delay is Zenith tropospheric delays (ZTD), which are estimated using the Precise Point Positioning (PPP) method. ZTD estimates can be beneficial for meteorological applications, for example, is the estimation of water vapor levels in the atmosphere from the estimated ZTD. We use GNSS data from the BAKO station in Cibinong and JOG2 station located in Yogyakarta. The GNSS data format is an Independent Exchange Receiver (RINEX), which we extracted using the sophisticated open-source GNSS software, called goGPS version 1.0 Beta from Geomatics Research and Development s.r.l. - Lomazzo, Italy. We validate the results of the extraction process with two international tropospheric products from International GNSS Services (IGS) with commercial software Bernese version 5 and the University of Nevada Reno (UNR) with software from NASA Jet Propulsion Laboratory (JPL) namely GIPSY / OASIS II. Epoch in this study, we use days of the year (DOY) 022-025 / 22-25 January representing the rainy season and DOY 230-233 to coincide on August 17-20 representing the dry season 2018. Our results obtained ZTD values both in January and August, and the two BAKO and JOG2 stations were consistent and worked well at different times and stations. RMS throughout DOY, both at BAKO and JOG2 stations, show small values <2 mm. The RMS value is relatively small, meaning that the troposphere estimation process with goGPS shows a good agreement because it is almost the same as the international troposphere products from UNR and IGS. This means that the ZTD estimation process from goGPS software can be an alternative to paid software. The range of ZTD values in January tends to be higher than in August, meaning the value of ZTD has a strong correlation with changes in the rainy and dry seasons, this shows that ZTD can be useful for meteorological purposes.

Keywords


Tropospheric Delay, GNSS, PPP, goGPS

Full Text:

PDF


References

Blewitt, G, W C Hammond, and C Kreemer. (2018). Harnessing the GPS data explosion for interdisciplinary science. EOS 99, DOI: 10.1029/2018EO104623.

Enge, P., & Misra, P. (2001). Global Positioning System (1 ed.). Ganga-Jamuna Press.

Enge, P., & Misra, P. (2006). Global Positioning System (2 ed.). Ganga-Jamuna Press.

Gabor, M. (1997, May 5). Remote Sensing of Water Vapor from GPS Receivers. Retrieved May 16, 2016, from http://www.csr.utexas.edu/texas_pwv/midterm/gabor/gabor.html#anchor561367.

Gatti, A., Tagliaferro, G., Realini, E. (2018). goGPS free and open-source GNSS software for tropospheric delay estimation. Proceedings from the conference held 4-13 April 2018 in Vienna, Austria, p.15590

goGPS_MATLAB. (2018). goGPS MATLAB is an advanced GNSS observation processing software. goGPS-project. https://github.com/goGPS-Project/goGPS_MATLAB (accessed April 2, 2018)

Herrera, A.M., Suhandri, H.F., Realini, E. et al. goGPS: open-source MATLAB software. GPS Solut 20, 595–603 (2016). https://doi.org/10.1007/s10291-015-0469-x

K. Yedukondalu, A. S. (2011). Estimation and Mitigation of GPS Multipath Interference Using Adaptive Filtering. Progress in Electromagnetics Research M(21), 133-148.

Koning, A. (2016). Precipitable water vapor estimation using GPS in Uganda: A study on obtaining the Zenith Wet Delay. Delft, The Netherlands

Nicholas, Z. (2016, October 04). Satellite and receiver clock errors. Retrieved from Tekmon Geomatics: http://www.tekmon.eu/1-3-2-satellite-and-receiver-clock-errors/

Realini, E. (2009) goGPS free and constrained relative kinematic positioning with low-cost receivers. Ph. D.thesis,http://www.researchgate.net/publication/237520116

Realini, E., Yoshida, D., Reguzzoni, M. et al. (2012). Enhanced satellite positioning as a web service with goGPS open-source software. Appl Geomat 4, 135–142 https://doi.org/10.1007/s12518-012-0081-5

Realini, E., Caldera, S., Pertusini, L., Sampietro, D. (2017) Precise GNSS positioning using smart devices Sensors 17 (10), 2434

Tagliaferro, G., Gatti, A., Realini, E. (2019). goGPS Open Source GNSS Software for Quasi-Static Applications: Latest Developments and Performance Tests. Geophysical Research Abstracts. 2019, Vol. 21, p1-1. 1p

Yuan, Y. K.-S. (2014). Real-time retrieval of precipitable water vapor from GPS precise point positioning. Journal of geophysical research: Atmospheres

Zumberge, J. F., Heftin, M. B., Jefferson, D. C., Watkins, M. M., and Webb, F. H. (1997). Precise point positioning for the efficient and robust analysis of GPS data from large networks. J. Geophys. Res. 102, 5005–5017. DOI: 10.1029/96JB03860



DOI: https://doi.org/10.22146/jgise.56071

Article Metrics

Abstract views : 1560 | views : 1939

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


Journal of Geospatial Information Science and Engineering (JGISE) ISSN: 2623-1182 (Online) Email: jgise.ft@ugm.ac.id The Contents of this website is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.