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TomoSAR Imaging for the Study of Forested Areas: A Virtual Adaptive Beamforming Approach

Martin del Campo Becerra, Gustavo Daniel and Shkvarko, Yuriy and Reigber, Andreas and Nannini, Matteo (2018) TomoSAR Imaging for the Study of Forested Areas: A Virtual Adaptive Beamforming Approach. Remote Sensing, 10 (11). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/rs10111822. ISSN 2072-4292.

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Official URL: https://www.mdpi.com/2072-4292/10/11/1822


Among the objectives of the upcoming space missions Tandem-L and BIOMASS, is the 3-D representation of the global forest structure via synthetic aperture radar (SAR) tomography (TomoSAR). To achieve such a goal, modern approaches suggest solving the TomoSAR inverse problems by exploiting polarimetric diversity and structural model properties of the different scattering mechanisms. This way, the related tomographic imaging problems are treated in descriptive regularization settings, applying modern non-parametric spatial spectral analysis (SSA) techniques. Nonetheless, the achievable resolution of the commonly performed SSA-based estimators highly depends on the span of the tomographic aperture; furthermore, irregular sampling and non-uniform constellations sacrifice the attainable resolution, introduce artifacts and increase ambiguity. Overcoming these drawbacks, in this paper, we address a new multi-stage iterative technique for feature-enhanced TomoSAR imaging that aggregates the virtual adaptive beamforming (VAB)-based SSA approach, with the wavelet domain thresholding (WDT) regularization framework, which we refer to as WAVAB (WDT-refined VAB). First, high resolution imagery is recovered applying the descriptive experiment design regularization (DEDR)-inspired reconstructive processing. Next, the additional resolution enhancement with suppression of artifacts is performed, via the WDT-based sparsity promoting refinement in the wavelet transform (WT) domain. Additionally, incorporation of the sum of Kronecker products (SKP) decomposition technique at the pre-processing stage, improves ground and canopy separation and allows for the utilization of different better adapted TomoSAR imaging techniques, on the ground and canopy structural components, separately. The feature enhancing capabilities of the novel robust WAVAB TomoSAR imaging technique are corroborated through the processing of airborne data of the German Aerospace Center (DLR), providing detailed volume height profiles reconstruction, as an alternative to the competing non-parametric SSA-based methods.

Item URL in elib:https://elib.dlr.de/126412/
Document Type:Article
Title:TomoSAR Imaging for the Study of Forested Areas: A Virtual Adaptive Beamforming Approach
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Martin del Campo Becerra, Gustavo DanielUNSPECIFIEDhttps://orcid.org/0000-0003-1642-6068UNSPECIFIED
Reigber, AndreasUNSPECIFIEDhttps://orcid.org/0000-0002-2118-5046UNSPECIFIED
Nannini, MatteoUNSPECIFIEDhttps://orcid.org/0000-0003-3523-9639UNSPECIFIED
Date:November 2018
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:Spatial spectral analysis (SSA); sum of Kronecker products (SKP); synthetic aperture radar (SAR) tomography (TomoSAR); virtual adaptive beamforming (VAB); wavelet transform (WT)
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 - Aircraft SAR
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute > SAR Technology
Deposited By: Martin del Campo Becerra, Gustavo
Deposited On:11 Feb 2019 08:23
Last Modified:02 Nov 2023 09:36

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