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Open AccessArticle

Effect of Helmert Transformation Parameters and Weight Matrix on Seasonal Signals in GNSS Coordinate Time Series

by Guo Chen 1,2, Qile Zhao 2,3,*, Na Wei 2,* and Min Li 2
1
School of Geodesy and Geomatics, Wuhan University, No. 129 Luoyu Road, Wuhan 430079, China
2
GNSS Research Center, Wuhan University, No. 129 Luoyu Road, Wuhan 430079, China
3
Collaborative Innovation Center of Geospatial Technology, Wuhan University, No. 129 Luoy Road, Wuhan 430079, China
*
Authors to whom correspondence should be addressed.
Sensors 2018, 18(7), 2127; https://doi.org/10.3390/s18072127
Received: 7 May 2018 / Revised: 28 June 2018 / Accepted: 29 June 2018 / Published: 3 July 2018
(This article belongs to the Section Remote Sensors)
Seasonal signals caused by the Earth’s surface mass redistribution can be detected by Global Navigation Satellite Systems (GNSS). The authors analyze the effect of Helmert transformation parameters and weight matrices, as well as the additional draconic signals on seasonal signals, in the GNSS coordinate time series. Moreover, the contribution of environmental loading models to the GNSS position series is assessed. Position time series of 647 global stations, with spans of 2–21 years are collected to generate six cumulative solutions using different parameters estimated in a deterministic model, as well as weight matrices. Comparison among the different solutions indicates that Helmert transformation parameters and weight matrices can result in a root mean square of 0.1 mm and 0.3 mm for seasonal signals, respectively. Compared to the displacements obtained from environmental loading models, seasonal signals estimated with the Helmert parameters and full weight matrices considered seems to have the best agreement with the results of the loading model. Meanwhile, the additional draconic signals are not effective to be parameterized in the deterministic model with an observation time span less than 15 years, marginally. There are 62%, 72% and 90% of 647 stations with weight root mean squares (WRMS) reduced by removing the loading-model-induced changes from the GNSS residual series for the east, north and vertical components, respectively. Finally, to obtain a velocity estimation with a bias of less than 0.1 mm/yr induced by seasonal signals, the position series with a time span greater than seven years is suggested. View Full-Text
Keywords: seasonal signals; environmental loading deformation; position series stacking; WRMS reduction; velocity bias seasonal signals; environmental loading deformation; position series stacking; WRMS reduction; velocity bias
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Chen, G.; Zhao, Q.; Wei, N.; Li, M. Effect of Helmert Transformation Parameters and Weight Matrix on Seasonal Signals in GNSS Coordinate Time Series. Sensors 2018, 18, 2127.

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