Paper Info
Title
Resolution Enhanced Sar Tomography: A Nonparametric Iterative Adaptive Approach
Abstract
The ground-volume separation of radar scattering plays an important role in the analysis of forested scenes. For this purpose, the data covariance matrix of multi-polarimetric (MP) multi-baseline (MB) SAR surveys can be represented thru a sum of two Kronecker products composed of the data covariance matrices and polarimetric signatures that correspond to the ground and canopy scattering mechanisms (SMs), respectively. The sum of Kronecker products (SKP) decomposition allows the use of different tomographic SAR focusing methods on the ground and canopy structural components separately, nevertheless, the main drawback of this technique relates to the rank-deficiencies of the resultant data covariance matrices, which restrict the usage of the adaptive beamforming techniques, requiring more advanced beamforming methods, such as compressed sensing (CS). This paper proposes a modification of the nonparametric iterative adaptive approach for amplitude and phase estimation (IAA-APES), which applied to MP-MB SAR data, serves as an alternative to the SKP-based techniques for ground-volume reconstruction, which main advantage relates precisely to the non-need of the SKP decomposition technique as a pre-processing step.
Year
DOI
Venue
2016
10.1109/IGARSS.2016.7729838
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
Keywords
Field
DocType
Amplitude and phase estimation (APES), compressed sensing (CS), SAR tomography (T-SAR), sum of Kronecker products (SKP)
Kronecker delta,Beamforming,Adaptive beamformer,Matrix (mathematics),Synthetic aperture radar,Computer science,Iterative method,Remote sensing,Compressed sensing,Covariance
Conference
ISSN
Citations 
PageRank 
2153-6996
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Gustavo D. Martin del Campo122.06
Andreas Reigber267070.53
Yuriy V. Shkvarko3377.69