The LSQR Algorithm for Inversion in Synthetic Aperture Imaging Radiometry

被引：0
|
作者：
Yang, Xiaocheng [1 ,2 ,3 ]
Huang, Jiaqi [2 ]
Lv, Wentao [1 ]
Wu, Long [1 ]
Jiang, Mingfeng [1 ]
Jin, Lingzi [4 ]
机构：
[1] Zhejiang Sci Tech Univ, Sch Informat Sci & Technol, Hangzhou, Zhejiang, Peoples R China
[2] Sunyard Syst Engn Co Ltd, Hangzhou, Zhejiang, Peoples R China
[3] Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou, Zhejiang, Peoples R China
[4] Zhejiang Gongshang Univ, Sch Comp & Informat Engn, Hangzhou, Zhejiang, Peoples R China
来源：
2017 10TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI) | 2017年
基金：
中国国家自然科学基金;
关键词：
synthetic aperture imaging radiometers; inverse problem; regularization; LSQR;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Since the problem of reconstructing the radiometric brightness temperature images in synthetic aperture imaging radiometers has been mathematically demonstrated to be ill-posed, it needs to be regularized to overcome its ill-conditioned properties. The LSQR iteration algorithm is proposed to retrieve brightness temperature images so as to provide a unique and stable solution. The performance is compared with the conventional minimum norm regularization based on the FPIR system. The simulation results show that the LSQR iteration algorithm can effectively reduce the reconstruction error, compared with the minimum norm regularization.
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页数：5
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