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

页码：1324 / 1329

页数：6

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