Three-Dimensional Surface Displacements From InSAR and GPS Measurements With Variance Component Estimation

Previous approaches that integrate interferometric synthetic aperture radar (InSAR) and GPS measurements for 3-D surface displacement mapping require statistically estimating the variances of the measurements to yield optimal results. We present a variance component estimation approach to weigh the...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2012-07, Vol.9 (4), p.754-758
Main Authors: Hu, Jun, Li, Zhi-Wei, Sun, Qian, Zhu, Jian-Jun, Ding, Xiao-Li
Format: Article
Language:English
Subjects:
3-D surface displacements
Accuracy
Atmospheric measurements
Atmospheric modeling
Displacement measurement
Estimation
Extraterrestrial measurements
Geographic information systems
Global Positioning System
Global positioning system (GPS)
Interferometric synthetic aperture radar
interferometric synthetic aperture radar (InSAR)
Optimization
Satellite navigation systems
Stochasticity
Three dimensional
Variance
variance component estimation (VCE)
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Description
Summary:Previous approaches that integrate interferometric synthetic aperture radar (InSAR) and GPS measurements for 3-D surface displacement mapping require statistically estimating the variances of the measurements to yield optimal results. We present a variance component estimation approach to weigh the InSAR and GPS measurements in deriving 3-D surface displacements. The approach exploits the observations themselves for determining the weighting scheme, and therefore the a priori information on the stochastic model of the observations is not required. This is of great importance as accurate knowledge on the stochastic model is often unavailable. The performance of the proposed method is validated with both simulated and real datasets.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2011.2181154