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Efficient InSAR Time Series Analysis in the Era of Big Data

Ansari, Homa and De Zan, Francesco and Bamler, Richard and Eineder, Michael (2017) Efficient InSAR Time Series Analysis in the Era of Big Data. Helmholtz Alliance: Remote Sensing and Earth System Dynamics - 5th Alliance Week, 26.-30. Jun. 2017, Garmisch-Partenkirchen, Germany.

Full text not available from this repository.

Abstract

Wide-swath satellite missions with short revisit times, such as Sentinel-1, provide an unprecedented wealth of interferometric time series and opens new opportunities for systematic monitoring of the Earth surface. The processing of the emerging Big Data with the state-of-the-art InSAR time series analysis techniques is, however, challenging. This contribution introduces a novel approach, named Sequential Estimator, for efficient estimation of the interferometric phase from long InSAR time series. The algorithm uses recursive estimation and analysis of the data covariance matrix via division of the data into small batches, followed by the compression of the data batches. From each compressed data batch artificial interferograms are formed, resulting in a strong data reduction. This scheme avoids the necessity of re-processing the entire data stack at the face of each new acquisition. It is shown that the proposed estimator introduces negligible degradation compared to the Cramér-Rao-Lower-Bound. The estimator may therefore be adapted for high-precision Near-Real-Time processing of InSAR and accommodate the conversion of InSAR from an off-line to a monitoring geodetic tool. The performance of the Sequential Estimator is compared to the state-of-the-art techniques via simulations and application to Sentinel-1 data.

Item URL in elib:https://elib.dlr.de/113678/
Document Type:Conference or Workshop Item (Speech)
Title:Efficient InSAR Time Series Analysis in the Era of Big Data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ansari, Homahoma.ansari (at) dlr.dehttps://orcid.org/0000-0002-4549-2497
De Zan, Francescofrancesco.dezan (at) dlr.deUNSPECIFIED
Bamler, Richardrichard.bamler (at) dlr.deUNSPECIFIED
Eineder, MichaelMichael.Eineder (at) dlr.dehttps://orcid.org/0000-0001-5068-1324
Date:2017
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Interferometric Synthetic Aperture Radar (InSAR), Big data, Distributed Scatterer Interferometry, Dimensionality Reduction, Low-Rank Approximation, Performance Analysis
Event Title:Helmholtz Alliance: Remote Sensing and Earth System Dynamics - 5th Alliance Week
Event Location:Garmisch-Partenkirchen, Germany
Event Type:Workshop
Event Dates:26.-30. Jun. 2017
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Tandem-L Vorstudien
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Ansari, Homa
Deposited On:16 Aug 2017 13:05
Last Modified:05 Sep 2017 17:36

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