Minimum Entropy via Subspace for ISAR Autofocus

被引：52

作者：

Cao, Pan ^{[1
]}

Xing, Mengdao ^{[1
]}

Sun, Guangcai ^{[1
]}

Li, Yachao ^{[1
]}

Bao, Zheng ^{[1
]}

机构：

[1] Xidian Univ, Key Lab Radar Signal Proc, Xian 710071, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2010年 / 7卷 / 01期

关键词：

Array manifold; autofocus; inverse synthetic aperture radar (ISAR); minimum entropy; signal subspace; TARGET;

D O I：

10.1109/LGRS.2009.2031658

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

In this letter, a novel approach to autofocus for inverse synthetic aperture radar (ISAR) imaging called minimum entropy via subspace autofocus is presented. This scheme uses the weighted signal subspace to express the phase errors left in the echoes after range-bin alignment and estimates the optimal weights sequentially via an optimization algorithm based on an entropy minimization principle, and its robustness and convergence can be ensured by the optimization method. Both the theoretical analysis and processing results of the real ISAR data have confirmed the feasibility of this new scheme.

引用

页码：205 / 209

页数：5

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