Spatiotemporal filtering using principal component analysis and Karhunen-Loeve expansion approaches for regional GPS network analysis

By D. Dong, Peng Fang, Yehuda Bock, F. Webb, Linette Prawirodirdjo, S. Kedar, Paul Jamason. 2006

345 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Geophysics, Oceanography

View Paper: https://www.semanticscholar.org/paper/dd5d7d7751cfe03b69b0ecba133565980edb8d92

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Alireza Amiri-Simkooei
2. Peter Teunissen

In Geophysics

1. Alireza Amiri-Simkooei
2. Yunzhong Shen
3. Bofeng Li

In Oceanography

1. Alireza Amiri-Simkooei
2. Yunzhong Shen

Citations in the corpus

• Spatiotemporal filtering of regional GNSS network’s position time series with missing data using principle component analysis (2013, methodology): “We show that the extended ‘stacking’ approach is a special case of our modified PCA approach when the spatial response is uniform.”
• Noise in multivariate GPS position time-series (2009, methodology): “We refer to Wdowinski et al. (1997), Nikolaidis (2002), Dong et al. (2006) and Teferle et al. (2006).”
• Blind source separation problem in GPS time series (2016, methodology): “The PCA technique has been widely applied in geodesy, both to filter common mode noise in GPS networks (e.g., Dong et al. 2006) and to detect regional tectonic signals (e.g., Kositsky and Avouac 2010; Ji and Herring 2011).”