Print Email Facebook Twitter QUInSAR: Temporal Parameter and Ambiguity Estimation Using Recursive Least-Squares Title QUInSAR: Temporal Parameter and Ambiguity Estimation Using Recursive Least-Squares: A Methodology for Persistent Scatterer Interferometry Author Verburg, Quintus (TU Delft Civil Engineering and Geosciences; TU Delft Geoscience and Remote Sensing) Contributor Hanssen, Ramon (mentor) van der Heuvel, Frank (mentor) van Leijen, Freek (mentor) Vossepoel, Femke (mentor) Degree granting institution Delft University of Technology Date 2017-08-31 Abstract Parameter and ambiguity estimation in the temporal domain, for arcs of differential phase observations between two persistent scatterers (PS), is a critical part in Persistent Scatterer Interferometry (PSI). Deformation models, used as constraint in the parameter estimation, often do not capture the full extent of the deformation behaviour. This results in a poor separation of signal and noise, and rejection of arcs that do not behave conform the functional model. Previous work assumed that deformation behaviour is stationary and that a full time series can be described with a single set of deformation parameters. In order to develop a more broadly applicable deformation model, this study applies a temporal smoothness constraint during parameter estimation, by assuming that deformation rates are affected by a temporally correlated zero-mean random acceleration. This constraint is implemented using recursive least-squares, similar to Kalman filtering, which also enables efficient updating of arcs when new acquisitions are available.Various kind of deformation types are simulated to create phase observations based on real TerraSAR-X, Radarsat2 and ERS stacks of interferograms. This simulated data is processed using the new recursive estimator and results are compared to that of a batch estimator using a steady-state assumption, to analyse the impact of adding a priori information about the smoothness of the physical signal. Furthermore, a case study on real data is performed on an area where non-linear subsidence has occurred, due to soil remediation. This study presents a mathematical framework for incorporating a priori knowledge about the smoothness of the deformation signal as constraint for parameter and ambiguity estimation. Especially non-linear deformation is better estimated using this method, resulting in a higher success-rate, better separation of signal and noise, and more PS passing quality thresholds. The framework moreover enables efficient updating of existing datasets when new acquisition are available. Subject InSARAdjustment theoryPSIRecursive least-squaresPhase unwrappingParameter estimationPersistent Scatterer Interferometry To reference this document use: http://resolver.tudelft.nl/uuid:5f071176-8737-4123-9b4e-292ae74fc028 Embargo date 2018-08-31 Part of collection Student theses Document type master thesis Rights © 2017 Quintus Verburg Files PDF 20170825_Thesis_Quintus_V ... _Final.pdf 13.21 MB Close viewer /islandora/object/uuid:5f071176-8737-4123-9b4e-292ae74fc028/datastream/OBJ/view