scholarly journals Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction

2021 ◽  
Author(s):  
Xingyu He ◽  
Ningning Tong ◽  
Tao Liu
Keyword(s):  
Synthetic Aperture Radar ◽  
Signal Reconstruction ◽  
Resolution Enhancement ◽  
Synthetic Aperture Radar Image ◽  
Image Resolution ◽  
Synthetic Aperture ◽  
Sparse Signal ◽  
Moving Target ◽  
Two Dimensional ◽  
Sparse Signal Reconstruction

The effect of synthetic aperture radar image resolution on target discrimination

2010 ◽  
Author(s):  
John E. McGowan ◽  
Steven C. Gustafson ◽  
Julie A. Jackson ◽  
Andrew J. Terzuoli, Jr.
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture Radar Image ◽  
Image Resolution ◽  
Radar Image ◽  
Synthetic Aperture ◽  
Target Discrimination ◽  
Aperture Radar

Permanent target for synthetic aperture radar image resolution assessment

2015 ◽  
Author(s):  
Yong-sheng Zhou ◽  
Chuan-rong Li ◽  
Ling-li Tang ◽  
Cai-xia Gao ◽  
Lu Ren ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture Radar Image ◽  
Image Resolution ◽  
Radar Image ◽  
Synthetic Aperture ◽  
Aperture Radar

scholarly journals Two-Dimensional ISAR Fusion Imaging of Block Structure Targets

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Xiaoxiu Zhu ◽  
Limin Liu ◽  
Baofeng Guo ◽  
Wenhua Hu ◽  
Lin Shi ◽  
...  
Keyword(s):  
Block Structure ◽  
Signal Reconstruction ◽  
Fusion Imaging ◽  
Sparse Signal ◽  
Observation Angle ◽  
Two Dimensional ◽  
Basis Matrix ◽  
Sparse Signal Reconstruction ◽  
Isar Imaging ◽  
Block Sparsity

The range resolution and azimuth resolution are restricted by the limited transmitting bandwidth and observation angle in a monostatic radar system. To improve the two-dimensional resolution of inverse synthetic aperture radar (ISAR) imaging, a fast linearized Bregman iteration for unconstrained block sparsity (FLBIUB) algorithm is proposed to achieve multiradar ISAR fusion imaging of block structure targets. First, the ISAR imaging echo data of block structure targets is established based on the geometrical theory of the diffraction model. The multiradar ISAR fusion imaging is transformed into a signal sparse representation problem by vectorization operation. Then, considering the block sparsity of the echo data of block structure targets, the FLBIUB algorithm is utilized to achieve the block sparse signal reconstruction and obtain the fusion image. The algorithm further accelerates the iterative convergence speed and improves the imaging efficiency by combining the weighted back-adding residual and condition number optimization of the basis matrix. Finally, simulation experiments show that the proposed method can effectively achieve block sparse signal reconstruction and two-dimensional multiradar ISAR fusion imaging of block structure targets.

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