GISAR Image Reconstruction Based 2-D Smoothed l0 Norm Minimization in Sparse Decomposition

被引：0
|
作者：
Lazarov, Andon [1 ]
Kabakchiev, Hristo [2 ]
Kostadinov, Todor [3 ]
Minchev, Dimitar [1 ]
机构：
[1] Burgs Free Univ, Dept Informat & Tech Sci, 64 San Stefano Str, Burgas 8000, Bulgaria
[2] Sofia Univ St Clement Ohrid, Dept Software Technol, Sofia 1164, Bulgaria
[3] Burgas Univ As Zlatarov, Dept Tech Sci, Burgas, Bulgaria
来源：
2015 16TH INTERNATIONAL RADAR SYMPOSIUM (IRS) | 2015年
关键词：
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：
General Inverse Synthetic Aperture Radar (GISAR) imaging algorithm based on two-dimensional (2-D) l0 norm minimization in signal sparse decomposition is discussed. GISAR geometry and kinematics are analytically described. GISAR signal model based on Linear Frequency Modulated (LFM) waveform is derived. The GISAR signal formation process is presented as a sparse decomposition in redundant Fourier basis. Image reconstruction procedure is presented as minimization of smooth norm of the image matrix. The algorithm of minimization of the number of non-zero point scatterers is thoroughly described. The results are illustrated by a numerical experiment.
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页码：416 / 421
页数：6
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