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Spectral Estimation for Synthetic Aperture Radar Tomography

Zhu, Xiao Xiang (2008) Spectral Estimation for Synthetic Aperture Radar Tomography. Master's, Technische Universität München.

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Official URL: http://www.espace-tum.de/mediadb/45303/45304/masterthesis_final.pdf


Synthetic Aperture Radar (SAR) Tomography, a new and advanced technique in the field of SAR processing, is aimed at determining the 3-D reflectivity function from measured multi-pass SAR data. It is essentially a spectrum estimation problem as for a specific resolution cell the complex valued SAR measurements of a SAR image stack are actually the irregularly sampled Fourier transform of the reflectivity function in the elevation direction. The successful launch of the German high resolution SAR mission TerraSAR-X provides a new possibility to investigate this topic with high quality spaceborne data. Within the framework of this master thesis, the spectrum estimation problem is formulated from a mathematical point of view. Different spectrum estimation strategies such as the Singular Value Decomposition (SVD) and Nonlinear Least Squares estimation (NLS) are evaluated and compared using both simulated data and TerraSAR-X data from the testsite Las Vegas with special consideration of the difficulties caused by sparse and irregularly spaced sampling. The problem of ill-conditioning when using the Singular Value Decomposition is investigated and regularization tools (such as singular value truncation and Wiener filtering) are utilized to overcome this problem. For the sake of validation, the spectrum estimation results with TerraSAR-X data are compared to the probable ground truth. Penalized model selection criteria such as the Bayesian Information Criterion (BIC), Akaike information criterion (AIC) and Minimum Description Length criterion (MDL) are implemented on the spectral estimates to determine the number of scatterers inside one resolution cell - which is necessary a prior knowledge for precise PSI displacement estimation. The probability of correctly detecting the number of scatterers and the accuracy of the corresponding elevation estimates are evaluated from simulated data. Finally, the model selection results with PS points of TerraSAR-X data are visualized in Google-Earth and the nature of PS pixel with multi-scatterers are discussed.

Item URL in elib:https://elib.dlr.de/92729/
Document Type:Thesis (Master's)
Title:Spectral Estimation for Synthetic Aperture Radar Tomography
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Date:September 2008
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Number of Pages:80
Keywords:Synthetic Aperture Radar (SAR), tomography, Spectrum estimation, Singular Value Decomposition, Nonlinear Least Squares estimation, Wiener filter, multi-scatterers, Model selection, penalized likelihood criterion, TerraSAR-X
Institution:Technische Universität München
Department:Lehrstuhl für Methodik der Fernerkundung
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 hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Zhu, Xiao Xiang
Deposited On:01 Dec 2014 10:10
Last Modified:31 Jul 2019 19:49

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