SAR ATR with full‐angle data augmentation and feature polymerisation-Reference-Cited by-同舟云学术

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SAR ATR with full‐angle data augmentation and feature polymerisation

Published:2019-07-12 Issue:19 Volume:2019 Page:6226-6230
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:J. eng.

Author:

Zhai Yikui¹,Ma Hui¹,Liu Jian¹,Deng Wenbo¹,Shang Lijuan¹,Sun Bing²,Jiang Ziyi³,Guan Huixin³,Zhi Yihang¹,Wu Xi¹,Zhou Jihua¹

Affiliation:

1. School of Information EngineeringWuyi UniversityJiangmenPeople's Republic of China

2. Scool of Electronics and Information EngineeringBeihang UniversityBeijingPeople's Republic of China

3. School of ComputerWuyi UniversityJiangmenPeople's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2019.0219

Reference14 articles.

1. Precision SAR processing using chirp scaling [J];Raney RK;IEEE Trans. Geosci. Remote Sens.,1994

2. Phase gradient autofocus – a robust tool for high resolution SAR phase correction;Wahl DE;IEEE Trans. Aerosp. Electron. Syst.,1994

3. SzegedyC LiuW JiaYet al.: ‘Going deeper with convolutions’.IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) Boston MA USA June 2015 pp.1–9 doi: 10.1109/CVPR.2015.7298594

4. RossTD WorrellSW VeltenVJet al.: ‘Standar SAR ATR evaluation experiments using the MSTAR public release data set’.Aerospace/Defense Sensing and Controls Int. Society for Optics and Photonics Orlando FL USA 1998 pp.566–573

5. TaoW XiC XiangweiRet al.: ‘Study on SAR target recognition based on support vector machine’.2009 2nd Asian‐Pacific Conf. on Synthetic Aperture Radar Xian China 2009 pp.856–859

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sparse Signal Models for Data Augmentation in Deep Learning ATR;Remote Sensing;2023-08-21

2. CNN Performance Analysis for SAR Object Classification;2022 23rd International Radar Symposium (IRS);2022-09-12

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