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Multiframe Transformation With Variance Component Estimation
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PRE
AI
DOI：10.1109/TGRS.2023.3302322.png)
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Abstract
En 中文
The modern global navigation satellite system (GNSS) technique is one of the most effective geoscience and remote sensing tool to observe crustal motions and quantify plate tectonics dynamics. Given multiple installed continuously operating GNSS observing stations, the multiframe transformation is implemented to connect the time-varying GNSS coordinates by the traditional stepwise method. Compared with the stepwise treatment of each pair of frames, the proposed structured total least-squares method considers the combined estimation for all frames, guaranteeing unique and consistent results for the multiframe symmetric transformation. Furthermore, we introduce the variance component (VC) as the nutshell and flexible indicator for land movement. The VCs can quantify the movement coordinatewise, regionalwise, or framewise if the VCs are estimable as we analyze. The simulated experiment shows that the multiframe symmetric transformation is statistically superior to the traditional stepwise treatment. For the application, the deformation caused by the Tohoku earthquake that happened in 2011 in northeast Japan is analyzed.
Keywords:
Errors-in-variables (EIV)
estimability analysis
land movement
multiframe
structured total least squares (TLS)
symmetric transformation
variance component estimation (VCE)
Journal
IF:
8.6
Papers:
2.1W
Citations:
10.7W
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