Three Dimensional ISAR Autofocus based on Sparsity Driven Motion Estimation

被引:0
|
作者
Hamad, Ahmad [1 ]
Ender, Joachim [1 ]
机构
[1] Univ Siegen, Ctr Sensor Syst ZESS, Siegen, Germany
来源
2020 21ST INTERNATIONAL RADAR SYMPOSIUM (IRS 2020) | 2020年
关键词
ISAR; Autofocus; Sparse Reconstruction; Compressed Sensing; 3D-ISAR; Motion Estimation;
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
Inverse Synthetic Aperture Radar (ISAR) exploits the motion of the target to achieve cross range imaging, as opposed to its range resolving capability (along line of sight) which relies on the bandwidth of the signal. In ISAR imaging, it is usually the case that the relative motion between the radar and the target of interest is unknown. The lack of precise knowledge of this relative motion affects the quality of the reconstructed image. Therefore, estimating the relative motion is an essential step for ISAR imaging. Compared to the two dimensional ISAR, the three dimensional ISAR imaging requires more motion components to be estimated. In this paper we present a sparsity driven algorithm that tackles the problem of three dimensional ISAR auto-focusing based on relative motion estimation.
引用
收藏
页码:51 / 56
页数:6
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