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题名:
2D normalized iterative hard thresholding algorithm for fast compressive radar imaging
作者: Li GX(李恭新); Yang J(杨佳); Yang WG(杨文广); Wang YC(王越超); Wang WX(王文学); Liu LQ(刘连庆)
作者部门: 机器人学研究室
通讯作者: Wang WX(王文学) ; Liu LQ(刘连庆)
关键词: fast compressive radar imaging ; compressive sensing ; two dimensional normalized iterative hard thresholding (2D-NIHT) algorithm ; compressive radar imaging model ; reconstruction performance
刊名: Remote Sensing
ISSN号: 2072-4292
出版日期: 2017
卷号: 9, 期号:6, 页码:1-16
收录类别: SCI ; EI
EI收录号: 20172603845516
WOS记录号: WOS:000404623900110
产权排序: 1
项目资助者: National Natural Science Foundation of China (Grant No. 61327014, Grant No. 61433017) and the CAS/SAFEA International Partnership Program for Creative Research Teams.
摘要: Compressive radar imaging has attracted considerable attention because it substantially reduces imaging time through directly compressive sampling. However, a problem that must be addressed for compressive radar imaging systems is the high computational complexity of reconstruction of sparse signals. In this paper, a novel algorithm, called two-dimensional (2D) normalized iterative hard thresholding (NIHT) or 2D-NIHT algorithm, is proposed to directly reconstruct radar images in the matrix domain. The reconstruction performance of 2D-NIHT algorithm was validated by an experiment on recovering a synthetic 2D sparse signal, and the superiority of the 2D-NIHT algorithm to the NIHT algorithm was demonstrated by a comprehensive comparison of its reconstruction performance. Moreover, to be used in compressive radar imaging systems, a 2D sampling model was also proposed to compress the range and azimuth data simultaneously. The practical application of the 2D-NIHT algorithm in radar systems was validated by recovering two radar scenes with noise at different signal-to-noise ratios, and the results showed that the 2D-NIHT algorithm could reconstruct radar scenes with a high probability of exact recovery in the matrix domain. In addition, the reconstruction performance of the 2D-NIHT algorithm was compared with four existing efficient reconstruction algorithms using the two radar scenes, and the results illustrated that, compared to the other algorithms, the 2D-NIHT algorithm could dramatically reduce the computational complexity in signal reconstruction and successfully reconstruct 2D sparse images with a high probability of exact recovery.
语种: 英语
WOS标题词: Science & Technology ; Technology
类目[WOS]: Remote Sensing
关键词[WOS]: SPARSE DECOMPOSITION ; SIGNAL RECOVERY ; MATRICES
研究领域[WOS]: Remote Sensing
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/20759
Appears in Collections:机器人学研究室_期刊论文

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作者单位: 1.State Key Laboratory of Robotics, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang 110016, China
2.University of the Chinese Academy of Sciences, Beijing 100049, China

Recommended Citation:
Li GX,Yang J,Yang WG,et al. 2D normalized iterative hard thresholding algorithm for fast compressive radar imaging[J]. Remote Sensing,2017,9(6):1-16.
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