A FAST SPARSE REPRESENTATION METHOD FOR SAR TARGET CONFIGURATION RECOGNITION

被引：0

作者：

Liu, Ming ^{[1
]}

Chen, Shichao ^{[2
]}

Lu, Fugang ^{[2
]}

Wang, Jun ^{[2
]}

Wu, Jie ^{[1
]}

Yang, Taoli ^{[3
]}

机构：

[1] Shaanxi Normal Univ, Sch Comp Sci, Xian 710119, Shaanxi, Peoples R China

[2] Xian Modern Control Technol Res Inst, Xian 710065, Shaanxi, Peoples R China

[3] Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Sichuan, Peoples R China

来源：

IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年

基金：

中国国家自然科学基金;

关键词：

Synthetic aperture radar (SAR) images; sparse representation (SR); target configuration recognition;

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：

Focusing on the problem of the real-time implementation in sparse representation (SR) based recognition algorithm, a fast sparse representation (FSR) algorithm is presented in this paper to improve the efficiency of synthetic aperture radar (SAR) target configuration recognition. Taking the inertia variance characteristic of SAR target images over a small range of azimuth angles into consideration, training samples of each configuration are averaged. Instead of using all the training samples to establish the dictionary in SR, the average samples are utilized to construct the dictionary in FSR. A small dictionary accelerates the speed of the proposed algorithm.

引用

页码：6999 / 7002

页数：4

共 7 条

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