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Study of Systematic Bias in Measuring Surface Deformation with SAR Interferometry

Ansari, Homa und De Zan, Francesco und Parizzi, Alessandro (2021) Study of Systematic Bias in Measuring Surface Deformation with SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 59 (2), Seiten 1285-1301. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2020.3003421. ISSN 0196-2892.

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Offizielle URL: https://ieeexplore.ieee.org/document/9130052

Kurzfassung

This article investigates the presence of a new interferometric signal in multilooked synthetic aperture radar (SAR) interferograms that cannot be attributed to the atmospheric or Earth-surface topography changes. The observed signal is short-lived and decays with the temporal baseline; however, it is distinct from the stochastic noise attributed to temporal decorrelation. The presence of such a fading signal introduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the estimation of Earth surface deformation from SAR time series. Here, the contribution of the mentioned phase component is quantitatively assessed. The biasing impact on the deformation-signal retrieval is further evaluated. A quality measure is introduced to allow the prediction of the associated error with the fading signals. Moreover, a practical solution for the mitigation of this physical signal is discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease significantly. Based on these analyses, we put forward our recommendations for efficient and accurate deformation-signal retrieval from large stacks of multilooked interferograms.

elib-URL des Eintrags:https://elib.dlr.de/135435/
Dokumentart:Zeitschriftenbeitrag
Titel:Study of Systematic Bias in Measuring Surface Deformation with SAR Interferometry
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Ansari, HomaHoma.Ansari (at) dlr.dehttps://orcid.org/0000-0002-4549-2497NICHT SPEZIFIZIERT
De Zan, Francescofrancesco.dezan (at) dlr.dehttps://orcid.org/0000-0002-1643-2559NICHT SPEZIFIZIERT
Parizzi, Alessandroalessandro.parizzi (at) dlr.dehttps://orcid.org/0000-0002-5651-8218NICHT SPEZIFIZIERT
Datum:Februar 2021
Erschienen in:IEEE Transactions on Geoscience and Remote Sensing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:59
DOI:10.1109/TGRS.2020.3003421
Seitenbereich:Seiten 1285-1301
Verlag:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:veröffentlicht
Stichwörter:Big Data, deformation estimation, differentialinterferometric synthetic aperture radar (SAR) (DInSAR),distributed scatterers (DSs), error analysis, near real-time (NRT)processing, phase inconsistencies, signal decorrelation, time-seriesanalysis
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben Multi-dimensionale SAR-Auswertung (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Methodik der Fernerkundung > SAR-Signalverarbeitung
Hinterlegt von: Ansari, Homa
Hinterlegt am:14 Jul 2020 12:01
Letzte Änderung:28 Jun 2023 13:56

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