Tucker Modeling based Kronecker Constrained Block Sparse Algorithm

This paper studies synthetic aperture radar (SAR) imaging problem which the scatterers are often distributed in block sparse pattern. To exploiting the sparse geometrical feature, a Kronecker constrained SAR imaging algorithm is proposed by combining the block sparse characteristics with the multiwa...

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Bibliographic Details
Published in:KSII transactions on Internet and information systems 2019-02, Vol.13 (2), p.657-667
Main Authors: Zhang, Tingping, Fan, Shangang, Li, Yunyi, Gui, Guan, Ji, Yimu
Format: Article
Language:Korean
Subjects:
compressed sensing
Kronecker structure
multiway block sparsity
SAR imaging
Tucker decomposition
Online Access:Get full text
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Summary:This paper studies synthetic aperture radar (SAR) imaging problem which the scatterers are often distributed in block sparse pattern. To exploiting the sparse geometrical feature, a Kronecker constrained SAR imaging algorithm is proposed by combining the block sparse characteristics with the multiway sparse reconstruction framework with Tucker modeling. We validate the proposed algorithm via real data and it shows that the our algorithm can achieve better accuracy and convergence than the reference methods even in the demanding environment. Meanwhile, the complexity is smaller than that of the existing methods. The simulation experiments confirmed the effectiveness of the algorithm as well.
ISSN:1976-7277
1976-7277