Block Compressive Sensing in Synthetic Aperture Radar (SAR)

被引：0
|
作者：
Kazemi, Peyman [1 ]
Modarres-Hashemi, Mahmood [1 ]
Naghsh, Mohammad Mahdi [1 ]
机构：
[1] Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan 8415683111, Iran
来源：
2016 24TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE) | 2016年
关键词：
Synthetic Aperture Radar (SAR); Compressive Sensing (CS); Block Compressive Sensing (BCS); Sparsity; Imaging; RECOVERY; SIGNALS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
High rate A/D's, heavy computations, large on board memories and downlink throughput are serious problems of high resolution Synthetic Aperture Radar (SAR). Compressive Sensing (CS) theory states that the sparsity or compressibility of a signal makes it possible to reconstruct the signal from a reduced number of samples. In the current paper, the Block Compressive sensing (BCS) is applied to SAR. This work proposes a new framework for SAR imaging in which a reconstruction method called BCS algorithm is used to achieve an excellent resolution with a few number of samples. The suggested technique can reconstruct images well by using nearly 1/3 samples in comparison with other CS image reconstruction methods.
引用
收藏
页码：1324 / 1329
页数：6
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