STATISTICAL REGULARIZATION IN SYNTHETIC APERTURE IMAGING RADIOMETRY

被引：0

作者：

Wu, Liang ^{[1
]}

Hu, Fei ^{[1
,2
]}

He, Feng ^{[1
,2
]}

Li, Jun ^{[1
]}

Peng, Xiaohui ^{[1
]}

Zhu, Dong ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan 430074, Peoples R China

[2] Huazhong Univ Sci & Technol, Natl Key Lab Sci & Technol Multispectral Informat, Wuhan 430074, Peoples R China

来源：

2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年

关键词：

Synthetic aperture imaging radiometers; inverse problem; statistical regularization;

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：

Synthetic aperture imaging radiometers (SAIRs) are powerful instruments for high-resolution observation of planetary surface at microwave band. In order to reconstruct the brightness temperature maps from the inteferometric measurements stably and uniquely, it has been recommended to cure the corresponding ill-posed problem with the aid of regularization framework. However, the performances of such numerical regularized solutions highly depend onmanually choosing the regularized parameters. In this study, we proposed a statistical regularization method to estimate the optimal regularized parameter of the SAIR inversion adaptively. Furthermore, we have carried out some numerical simulations in reference to the SAIR inversion, and relative comparative analysis has been accomplished to validate the proposed method.

引用

页码：4726 / 4729

页数：4

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