FMCW SAR Imaging Based on Compressed Sensing

2020 ◽  
Author(s):  
Jingyi Qian ◽  
Dongzhi Chen ◽  
Weizhong Yan
Keyword(s):  
Compressed Sensing ◽  
Sar Imaging

Information Capacity and Sampling Ratios for Compressed Sensing-Based SAR Imaging

2015 ◽  
Vol 12 (4) ◽  
pp. 900-904 ◽  
Author(s):  
Jianzhong Guo ◽  
Jingxiong Zhang ◽  
Ke Yang ◽  
Bingchen Zhang ◽  
Wen Hong ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Information Capacity ◽  
Sar Imaging

scholarly journals AZIMUTH MULTICHANNEL SAR IMAGING BASED ON COMPRESSED SENSING

2013 ◽  
Vol 141 ◽  
pp. 497-516 ◽  
Author(s):  
Mingjiang Wang ◽  
Weidong Yu ◽  
Robert Wang
Keyword(s):  
Compressed Sensing ◽  
Sar Imaging

Random-Frequency SAR Imaging Based on Compressed Sensing

2013 ◽  
Vol 51 (2) ◽  
pp. 983-994 ◽  
Author(s):  
Jungang Yang ◽  
John Thompson ◽  
Xiaotao Huang ◽  
Tian Jin ◽  
Zhimin Zhou
Keyword(s):  
Compressed Sensing ◽  
Sar Imaging ◽  
Random Frequency

Compressed sensing technique for circular SAR imaging

2009 ◽  
Author(s):  
Yun Lin ◽  
Wen Hong ◽  
Wei-xian Tan ◽  
Yan-ping Wang
Keyword(s):  
Compressed Sensing ◽  
Sar Imaging

scholarly journals A Novel Motion Compensating Method for MIMO-SAR Imaging Based on Compressed Sensing

2015 ◽  
Vol 15 (4) ◽  
pp. 2157-2165 ◽  
Author(s):  
Fu-Fei Gu ◽  
Qun Zhang ◽  
Long Chi ◽  
Yong-An Chen ◽  
Song Li
Keyword(s):  
Compressed Sensing ◽  
Sar Imaging

scholarly journals MIMO SAR Imaging for Wide-Swath Based on Compressed Sensing

2017 ◽  
Vol 2017 ◽  
pp. 1-13
Author(s):  
Feng Liu ◽  
Shanxiang Mu ◽  
Wanghan Lv
Keyword(s):  
Compressed Sensing ◽  
Random Phase ◽  
Zero Point ◽  
Compressive Sampling ◽  
Hardware Complexity ◽  
Range Imaging ◽  
Digital Beamforming ◽  
Range Ambiguity ◽  
Sar Imaging ◽  
Wide Swath

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. Random phase orthogonal waveform (RPOW) is designed for MIMO SAR based on compressed sensing (CS). Echo model of sparse array in range and compressive sampling is reconstructed with CS theory. Resolution in range imaging is improved by using the techniques of digital beamforming (DBF) in transmit. Zero-point technique based on CS is proposed with DBF in receive and the range ambiguity is suppressed effectively. Comprehensive numerical simulation examples are performed. Its validity and practicality are validated by simulations.

High-Resolution Millimeter-Wave Ground-Based SAR Imaging via Compressed Sensing

2018 ◽  
Vol 54 (3) ◽  
pp. 1-4 ◽  
Author(s):  
Sang-Hoon Jung ◽  
Yong-Sun Cho ◽  
Rae-Seoung Park ◽  
Jong-Mann Kim ◽  
Hyun-Kyo Jung ◽  
...  
Keyword(s):  
High Resolution ◽  
Compressed Sensing ◽  
Millimeter Wave ◽  
Sar Imaging

Quadratic Compressed Sensing Based SAR Imaging Algorithm for Phase Noise Mitigation

2016 ◽  
Vol E99.A (6) ◽  
pp. 1233-1237 ◽  
Author(s):  
Xunchao CONG ◽  
Guan GUI ◽  
Keyu LONG ◽  
Jiangbo LIU ◽  
Longfei TAN ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Phase Noise ◽  
Noise Mitigation ◽  
Imaging Algorithm ◽  
Sar Imaging
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