Abstract
The high-accuracy GPS velocity field is one of effective approaches to study the regional crustal displacement, and can provide validations and constraints for GIA models. There are spatially and temporally correlated errors in GPS data. Applying a spatiotemporal filter can reduce these effects and improve the accuracy of GPS time series. To obtain high-accuracy GPS vertical velocities in Antarctic peninsula, a “regional filter” is used to remove the spatially correlated errors in the selected 6 GPS time series, and the classic autocorrelation function is used to mitigate the temporally correlated errors of each GPS time series. The result shows that the scatter of GPS time series is reduced significantly after spatiotemporal filtering, the reduction of maximum RMS can reach up to 41.82%, and mean RMS reduction is 35.44%.
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Acknowledgements
This work is supported by the State Key Program of National Science of China (41531069), the State Program of National Science of China (41176173), and Chinese Polar Environment Comprehensive Investigation and Assessment Programs (CHINARE2017).
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Li, W., Li, F., Zhang, S., Lei, J., Zhang, Q. (2018). Analysis of GPS Time Series Based on Spatio-temporal Filtering in Antarctic Peninsula. In: Sun, J., Yang, C., Guo, S. (eds) China Satellite Navigation Conference (CSNC) 2018 Proceedings. CSNC 2018. Lecture Notes in Electrical Engineering, vol 498. Springer, Singapore. https://doi.org/10.1007/978-981-13-0014-1_58
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DOI: https://doi.org/10.1007/978-981-13-0014-1_58
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