Constrained Recursive Parameter Estimation for InSAR ARCS

Conference paper (2024)

Authors

Y. Wang Mathematical Geodesy and Positioning -

W.S. Brouwer Mathematical Geodesy and Positioning -

F.J. van Leijen Mathematical Geodesy and Positioning -

R.F. Hanssen Mathematical Geodesy and Positioning -

Research Group

Mathematical Geodesy and Positioning () (TU Delft)

Parameter estimation Recursive least-squares InSAR point scatterers Smoothness constraints

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Published Date

2024

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Geoscience and Remote Sensing

Research Group

Mathematical Geodesy and Positioning

Abstract

The growing availability of SAR data offers a real-time deformation monitoring opportunity, but data utilization can be inefficient. Our study introduces a mathematical framework using recursive least-squares and the wrapped phase, allowing efficient updates when new data arrives. This method also incorporates prior knowledge about signal smoothness for non-linear displacement estimation. Compared to the batch solution, our recursive approach achieves parameter estimation without storing past measurements while respecting signal smoothness constraints.

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