Sparse microwave imaging： Principles and applications

This paper provides principles and applications of the sparse microwave imaging theory and technology. Synthetic aperture radar （SAR） is an important method of modern remote sensing. During decades microwave imaging technology has achieved remarkable progress in the system performance of microwave i...

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Bibliographic Details
Published in:Science China. Information sciences 2012-08, Vol.55 (8), p.1722-1754
Main Authors: Zhang, BingChen, Hong, Wen, Wu, YiRong
Format: Article
Language:English
Subjects:
Algorithms
Computer Science
Image enhancement
Image quality
Image reconstruction
Imaging
Information Systems and Communication Service
Microwaves
Performance evaluation
Principles
Radar
Radar imaging
Reconstruction
Reduction
Remote sensing
Review
Signal processing
Synthetic aperture radar
信号处理理论
合成孔径雷达
应用
微波成像
成像原理
成像技术
稀疏表示
雷达成像
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Summary:This paper provides principles and applications of the sparse microwave imaging theory and technology. Synthetic aperture radar （SAR） is an important method of modern remote sensing. During decades microwave imaging technology has achieved remarkable progress in the system performance of microwave imaging technology, and at the same time encountered increasing complexity in system implementation. The sparse microwave imaging introduces the sparse signal processing theory to radar imaging to obtain new theory, new system and new methodology of microwave imaging. Based on classical SAR imaging model and fundamental theories of sparse signal processing, we can derive the model of sparse microwave imaging, which is a sparse measurement and recovery problem and can be solved with various algorithms. There exist several fundamental points that must be considered in the efforts of applying sparse signal processing to radar imaging, including sparse representation, measurement matrix construction, unambiguity reconstruction and performance evalua- tion. Based on these considerations, the sparse signal processing could be successfully applied to radar imaging, and achieve benefits in several aspects, including improvement of image quality, reduction of data amount for sparse scene and enhancement of system performance. The sparse signal processing has also been applied in several specific radar imaging applications.
ISSN:1674-733X
1869-1919
DOI:10.1007/s11432-012-4633-4