Proceedings Article10.1109/CIE-RADAR.2011.6159838
A novel SAR imaging algorithm based on compressed sensing
Junfei Chang,Wei Zhang,Shunsheng Zhang,Jing Li +3 more
- 01 Oct 2011
- Vol. 2, pp 1467-1470
TL;DR: Experimental results show the presented algorithm based on compressed sensing have a better performance than the conventional SAR algorithm even with only smaller samples, and also indicate that the presented algorithms is robustness with existence of serious noise.
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Abstract: High speed A/D sampling and large scale data storage are two basic challenges of the high resolution SAR system. The developing of radar system is limited by these two challenges under the Nyquist sampling theory. Compressed sensing (CS) is a new approach of sparse signals recovered beyond the constraints of Nyquist sampling technique. With the consideration of these problems that might happen and the advantage of CS theory, a novel SAR image processing algorithm based on compressive sensing was proposed in this paper. Using the data whose sampling rate is lower than the required Nyquist sampling rate, the CS-based algorithm operates at range and azimuth dimensional respectively. Experimental results show the presented algorithm based on compressed sensing have a better performance than the conventional SAR algorithm even with only smaller samples, and also indicate that the presented algorithm is robustness with existence of serious noise
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Citations
Analysis of the effect of sparsity on the performance of SAR imaging based on CS theory
Jieqiong Zhang,Bing Sun,Hailun Xu +2 more
- 01 Apr 2016
TL;DR: The result shows that for the targets outside the scene of the coefficient lattice, the imaging method based on compressive sensing theory can not improve the sidelobe's performance of the imaging result.
2
MIMO SAR Imaging for Wide-Swath Based on Compressed Sensing
Feng Liu,Shanxiang Mu,Wanghan Lv +2 more
TL;DR: To reduce the amount of data to be stored and software/hardware complexity and suppress range ambiguity, a novel MIMO SAR imaging based on compressed sensing is proposed under the condition of wide-swath imaging.
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