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On the Definition of an Independent Stochastic Model for InSAR Time Series

On the Definition of an Independent Stochastic Model for InSAR Time Series

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1109/TGRS.2025.3600893. This is version 2 of this Preprint.

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Authors

Wietske S Brouwer, Ramon Hanssen 

Abstract

InSAR enables the estimation of displacements of (objects on) the Earth’s surface. To provide reliable estimates, both an independent stochastic and functional model are re- quired. However, the intrinsic problem of InSAR is that both are unknown. Here we propose an independent definition of the stochastic model, via an approximation scheme for the variance- covariance matrix for double-differenced phase observations for an arc, i.e., the phase difference between two points relative to a reference epoch. Detecting temporal partitions in the amplitude time series, we assign quality values to all phase observations within each partition. To reduce the impact of outliers, we introduce the Normalized Median Absolute Deviation (NMAD) of the vector of amplitudes to robustly estimate the variance of the phase observations. The method results in a scatterer-specific and time-variable stochastic model, which is independent of the phase observations itself and prior to parameter estimation. This differs from many conventional methods where the quality is often determined a posteriori from the residuals between the model and the observations. This yields more realistic and reliable displacement estimates, as well as improved statements on the precision and reliability of the estimated parameters.

DOI

https://doi.org/10.31223/X5RX42

Subjects

Engineering, Physical Sciences and Mathematics

Keywords

InSAR, surface displacements, stochastic model, parameter estimation, surface deformation, stochastic model, Parameter estimation

Dates

Published: 2025-01-16 08:35

Last Updated: 2025-08-28 11:44

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License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None