Share:


Considering variances of quasi-random effects in relative GPS positioning performed during daytime and nighttime periods – a novel two-stage approach

    Darko Anđić Affiliation

Abstract

In this paper, a new two-stage approach, involving an integral treatement of all quasi-random effects limiting the accuracy of relative GPS positioning and the method of moments to obtain final variance components regarding the effects of short-term (“far-field”) multipath (factor b), joint action of long-term (“near-field”) multipath and receiver antenna phase center offset and variations (factor a1), as well as joint action of tropospheric and ionospheric refraction (factor a2), is presented. In the study, GPS data collected on five baselines were used. Variance components of the quasirandom effects were obtained for the three relative GPS coordinates (e, n and u) using individually monthly datsets including daytime- and those including nighttime-wise ambiguity-fixed baseline solutions. The related results show that statistically significant inequality exists when comparing corresponding variances obtained for daytime and nighttime periods. It turned out that the following standard deviation estimates intervals are present (by the coordinates e, n and u, respectively): (a) daytime period: 3.3–6.9, 4.6–9.0 and 9.1–20.3 mm (factor b); 1.5–4.7, 1.9–7.0 and 3.4–21.9 mm (factor 1a ); 0.0116– 0.3282, 0.0103–0.2365 and 0.1222–0.7818 mm/km (factor a2); (b) nighttime period: 3.2–4.9, 4.7–7.3 and 8.4–15.4 mm (factor b); 0.8–3.8, 2.1–5.0 and 3.1–15.8 mm (factor a1); 0.0118–0.2734, 0.0097–0.2289 and 0.0752–0.6315 mm/km (factor a2).

Keyword : relative GPS positioning, quasi-random effects, variance components, ANOVA estimates, method of moments, sub-daily impacts, statistical hypotheses testing

How to Cite
Anđić, D. (2021). Considering variances of quasi-random effects in relative GPS positioning performed during daytime and nighttime periods – a novel two-stage approach. Geodesy and Cartography, 47(1), 27-33. https://doi.org/10.3846/gac.2021.12303
Published in Issue
Apr 8, 2021
Abstract Views
421
PDF Downloads
327
Creative Commons License

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

References

Anđić, D. (2016). Variance components estimation of residual errors in GPS precise positioning. Geodetski vestnik, 60(3), 467–482. https://doi.org/10.15292/geodetski-vestnik.2016.03.467-482

Anđić, D. (2019a). Seasonal pattern in time series of variances of GPS residual errors ANOVA estimates. Geodetski vestnik, 63(2), 260–271. https://doi.org/10.15292/geodetski-vestnik.2019.02.260-271

Anđić, D. (2019b). Određivanje komponenti disperzija vremenski varijabilnih grešaka u GPS određivanju koordinata [Estimation of time-variable error variance components in GPS determination of coordinates] [Doctoral dissertation]. University of Belgrade, Serbia (in Serbian). https://doi.org/10.13140/RG.2.2.19498.36808/2

Deng, L., Jiang, W., Li, Z., Chen, H., Wang, K., & Ma, Y. (2016). Assesment of second- and third-order ionospheric effects on regional networks: Case study in China with longer CMONOC GPS coordinate series. Journal of Geodesy, 91(2), 1–21. https://doi.org/10.1007/s00190-016-0957-y

Elsobeiey, M., & El-Diasty, M. (2016). Impact of tropospheric delay gradients on total tropospheric delay and precise point positioning. International Journal of Geosciences, 7(5), 645–654. https://doi.org/10.4236/ijg.2016.75050

Han, K., Tang, C., & Deng, Z. (2019). A new method for multipath filtering in GPS static high-precision positioning. Sensors, 19(12), 2704. https://doi.org/10.3390/s19122704

Hu, Z., Zhao, Q., Chen, G., Wang, G., Dai, Z., & Li, T. (2015). First results of field absolute calibration of the GPS receiver antenna at Wuhan University. Sensors, 15(11), 28717–28731. https://doi.org/10.3390/s151128717

Jadviščok, P., Ovesná, G., & Konečný, M. (2016). Multipath and its manifestations in the real environment of geodetic practice. Geodesy and Cartography, 42(2), 47–52. https://doi.org/10.3846/20296991.2016.1198573

Juni, I., & Rózsa, S. (2019). Validation of a new model for the estimation of residual tropospheric delay error under extreme weather conditions. Periodica Polytechnica Civil Engineering, 63(1), 121–129. https://doi.org/10.3311/PPci.12132

Kallio, U., Koivula, H., Lahtinen, S., Nikkonen, V., & Poutanen, M. (2019). Validating and comparing GNSS antenna calibrations. Journal of Geodesy, 93, 1–18. https://doi.org/10.1007/s00190-018-1134-2

Klos, A., Hunegnaw, A., Teferle, F. N., Abraha, K. E., Ahmed, F., & Bogusz, J. (2018). Statistical significance of trends in Zenith Wet Delay from re-processed GPS solutions. GPS Solutions, 22(2), 51. https://doi.org/10.1007/s10291-018-0717-y

Snedecor, G. W., & Cochran, W. G. (1989). Statistical methods (8th ed.). Ames.

Zhou, Y., Kuang, C., & Cai, C. (2018). Analysis of high-order ionospheric effects on GNSS precise point positioning in the China area. Survey Review, 51(368), 442–449. https://doi.org/10.1080/00396265.2018.1478483