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Mixed sparse representation for approximated observation-based compressed sensing radar imaging

文献类型：期刊论文

作者Li, Bo1,2; Liu, Falin1,2; Zhou, Chongbin1,2; Wang, Zheng1,2; Han, Hao1,2
刊名JOURNAL OF APPLIED REMOTE SENSING
出版日期2018-09-10
卷号12期号:3页码:20
关键词synthetic aperture radar mixed sparse representation compressed sensing magnitude-phase separation approximated observation
ISSN号1931-3195
DOI10.1117/1.JRS.12.035015
通讯作者Liu, Falin(liufl@ustc.edu.cn)
英文摘要Recently, compressed sensing (CS) has been applied in synthetic aperture radar (SAR). A framework of mixed sparse representation (MSR) has been proposed for reconstructing SAR images due to the complicated ground features. The existing method decomposes the image into the point and smooth components, where the sparse constraint is directly applied to the smooth components. This makes it difficult to tackle the complex-valued SAR images, since the phase angles of SAR images are always stochastic. A magnitude-phase separation MSR method is proposed for CS-SAR imaging based on approximated observation. Compared to the existing method, the proposed method has better reconstruction ability, because it only imposes the sparse constraint on the magnitude of the smooth components, and therefore, the phase angles are still stochastic. Furthermore, owing to the inherent low memory requirement of approximated observation, the proposed method requires much less memory cost. In the simulation and experimental results, the proposed method deals with the complex-valued SAR images effectively and demonstrates superior performance over the chirp scaling algorithm and the existing MSR method. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
WOS关键词GROUND-PENETRATING RADAR ; SAR ; ALGORITHM ; REGULARIZATION ; GENERATION ; ERROR
资助项目National Natural Science Foundation of China[61431016] ; National Natural Science Foundation of China[61771446]
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000444125200001
出版者SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/38731]  
专题中国科学院合肥物质科学研究院
通讯作者Liu, Falin
作者单位1.Chinese Acad Sci, Key Lab Electromagnet Space Informat, Hefei, Anhui, Peoples R China
2.Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei, Anhui, Peoples R China
推荐引用方式
GB/T 7714		 Li, Bo,Liu, Falin,Zhou, Chongbin,et al. Mixed sparse representation for approximated observation-based compressed sensing radar imaging[J]. JOURNAL OF APPLIED REMOTE SENSING,2018,12(3):20.
APA Li, Bo,Liu, Falin,Zhou, Chongbin,Wang, Zheng,&Han, Hao.(2018).Mixed sparse representation for approximated observation-based compressed sensing radar imaging.JOURNAL OF APPLIED REMOTE SENSING,12(3),20.
MLA Li, Bo,et al."Mixed sparse representation for approximated observation-based compressed sensing radar imaging".JOURNAL OF APPLIED REMOTE SENSING 12.3(2018):20.

入库方式： OAI收割

来源：合肥物质科学研究院

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