Remote Sensing Applications and Decision Support

Digital beamforming synthetic aperture radar imaging on received signals based on compressed sensing

[+] Author Affiliations
Mingjiang Wang, Lei Guo, Xiulian Luo

Chinese Academy of Sciences, Institute of Electronics, Department of Space Microwave Remote Sensing System, No. 19 North 4th Ring Road West, Haidian District, Beijing 100190, China

University of the Chinese Academy of Sciences, School of Electronic, Electrical and Communication Engineering, No.19A Yuquan Road, Beijing 100049, China

Weidong Yu, Robert Wang

Chinese Academy of Sciences, Institute of Electronics, Department of Space Microwave Remote Sensing System, No. 19 North 4th Ring Road West, Haidian District, Beijing 100190, China

J. Appl. Remote Sens. 9(1), 096060 (Apr 24, 2015). doi:10.1117/1.JRS.9.096060
History: Received January 2, 2015; Accepted March 31, 2015
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Abstract.  Digital beamforming synthetic aperture radar (SAR) in elevation is a promising technique to realize the increasing requirements of high-resolution and wide-swath imaging in remote sensing, although it suffers from a dense sampling rate and heavy data volume. This poses serious challenges to onboard transmission and storage of satellites. Additionally, the traditional beamforming technique suffers degraded imaging capacities caused by the incoherence between the received signals of different channels. To overcome these deficiencies, this paper proposes an improved method for the focusing of multichannel SAR raw data based on the framework of compressed sensing (CS). Through adaptive measurement matrix construction for each subchannel, the proposed approach can take the misregistration information of all received signals into account, providing an accurate imagery recovery of sparse reflectivity. Compared with conventional processing, the suggested technique not only provides a more efficient data acquisition scheme for orbital configurations, but also carries the potential to eliminate the migration effects of imaging amplitude and resolution. Furthermore, it is demonstrated that the proposed implementation is equipped with additional imaging benefits, such as superresolution and lower sidelobes. Numerical and experimental results have validated these favorable performances of the suggested strategy.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Mingjiang Wang ; Weidong Yu ; Robert Wang ; Lei Guo and Xiulian Luo
"Digital beamforming synthetic aperture radar imaging on received signals based on compressed sensing", J. Appl. Remote Sens. 9(1), 096060 (Apr 24, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096060


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