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Sparse SAR Imaging Based on Periodic Block Sampling Data

delete2022-01-01
delete14
PRE
AI
H
Hui Bi *
X
Xingmeng Lu
W
Weixing Yang
朱
朱岱寅 (Daiyin Zhu)
DOI:10.1109/TGRS.2021.3110772delete
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Abstract

Abstract

En 中文
Recently, a novel design scheme of low-earth-orbit spaceborne mini-synthetic aperture radar (MiniSAR) system is proposed to exploit the integrated transceiver to collect the azimuth periodic block sampling data by using alternated transmitting and receiving operations. Because such collected data are downsampled, the images recovered by the typical matched filtering (MF)-based methods have the problems of obvious azimuth ambiguities, ghosts, and energy dispersion. To find a suitable method for such data, with the help of sparse signal processing technique, we first introduce sparse synthetic aperture radar (SAR) imaging with l(1)-norm regularization-based approximated observation method to recover the large-scale considered scene. To further improve the imaging performance, a novel approximated observation unambiguous sparse SAR imaging method via l(2,1)-norm is proposed. Compared with l(1)-norm-based method, the recovered image by the proposed one achieves better imaging quality with reduced azimuth ambiguities and ghosts. Experimental results on simulated and real data validate the proposed method.
Keywords:
Periodic block sampling
spaceborne synthetic aperture radar (SAR) system
sparse synthetic aperture radar (SAR) imaging
sparse unambiguous reconstruction
synthetic aperture radar (SAR)

Journal

IEEE Transactions on Geoscience and Remote Sensing cover
IEEE Transactions on Geoscience and Remote Sensing
IF:
8.6
Papers:
2.2W
Citations:
10.7W

Organization

No organization information available
Cited Papers

Cited Papers

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Sparse microwave imaging: Principles and applications
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Compressed Synthetic Aperture Radar
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errPatel, Vishal M.; Easley, Glenn R.; Healy, Dennis M., Jr.; Chellappa, Rama
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L1-Regularization-Based SAR Imaging and CFAR Detection via Complex Approximated Message Passing
err2017-06-01
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errBi, Hui; Zhang, Bingchen; Zhu, Xiao Xiang; Hong, Wen; Sun, Jinping; Wu, Yirong
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From Theory to Application: Real-Time Sparse SAR Imaging
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errBi, Hui; Bi, Guoan; Zhang, Bingchen; Hong, Wen; Wu, Yirong
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