On the Stochastic Model for InSAR Single Arc Point Scatterer Time Series

Conference Paper (2023)
Author(s)

W.S. Brouwer (TU Delft - Mathematical Geodesy and Positioning)

Yuqing Wang (TU Delft - Mathematical Geodesy and Positioning)

FJ Van Leijen (TU Delft - Mathematical Geodesy and Positioning)

R. F. Hanssen (TU Delft - Mathematical Geodesy and Positioning)

Research Group
Mathematical Geodesy and Positioning
Copyright
© 2023 W.S. Brouwer, Y. Wang, F.J. van Leijen, R.F. Hanssen
DOI related publication
https://doi.org/10.1109/IGARSS52108.2023.10282629
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 W.S. Brouwer, Y. Wang, F.J. van Leijen, R.F. Hanssen
Research Group
Mathematical Geodesy and Positioning
Pages (from-to)
7902-7905
ISBN (electronic)
9798350320107
Reuse Rights

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Abstract

InSAR enables the estimation of displacements of (objects on) the earth's surface. To provide reliable estimates, both a stochastic and mathematical model are required. However, the intrinsic problem of InSAR is that both are unknown. Here we derive the Variance-Covariance Matrix (VCM) for double differenced phase observations for an arc, i.e., the phase difference between two points relative to a reference epoch. Using the Normalized Amplitude Dispersion we subdivide the time series in multiple partitions. The method results in a more realistic stochastic model, and consequently more realistic and reliable displacement parameters. The stochastic model also allows to make statements on the precision and reliability of the estimated parameters.

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