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SAR Tomography via Nonlinear Blind Scatterer Separation

Wang, Yuanyuan and Zhu, Xiao Xiang (2021) SAR Tomography via Nonlinear Blind Scatterer Separation. IEEE Transactions on Geoscience and Remote Sensing, pp. 1-14. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2020.3022209. ISSN 0196-2892. (In Press)

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Official URL: https://ieeexplore.ieee.org/document/9200699

Abstract

Layover separation has been fundamental to many synthetic aperture radar applications, such as building reconstruction and biomass estimation. Retrieving the scattering profile along the mixed dimension (elevation) is typically solved by inversion of the SAR imaging model, a process known as SAR tomography. This paper proposes a nonlinear blind scatterer separation method to retrieve the phase centers of the layovered scatterers, avoiding the computationally expensive tomographic inversion. We demonstrate that conventional linear separation methods, e.g., principle component analysis (PCA), can only partially separate the scatterers under good conditions. These methods produce systematic phase bias in the retrieved scatterers due to the nonorthogonality of the scatterers steering vectors, especially when the intensities of the sources are similar or the number of images is low. The proposed method artificially increases the dimensionality of the data using kernel PCA, hence mitigating the aforementioned limitations. In the processing, the proposed method sequentially deflates the covariance matrix using the estimate of the brightest scatterer from kernel PCA. Simulations demonstrate the superior performance of the proposed method over conventional PCA-based methods in various respects. Experiments using TerraSAR-X data show an improvement in height reconstruction accuracy by a factor of one to three, depending on the used number of looks.

Item URL in elib:https://elib.dlr.de/135884/
Document Type:Article
Additional Information:So2Sat
Title:SAR Tomography via Nonlinear Blind Scatterer Separation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Wang, YuanyuanYuanyuan.Wang (at) dlr.deUNSPECIFIED
Zhu, Xiao XiangDLR-IMF/TUM-SiPEOUNSPECIFIED
Date:2021
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.1109/TGRS.2020.3022209
Page Range:pp. 1-14
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:0196-2892
Status:In Press
Keywords:blind source separation; kernel PCA; multibaseline InSAR; nonlinear kernel; SAR tomography
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Wang, Yuanyuan
Deposited On:07 Sep 2020 09:54
Last Modified:14 Jan 2021 17:23

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