Forward-Looking Super-Resolution Radar Imaging via Reweighted L1-Minimization

被引：0
|
作者：
Lee, Hyukjung [1 ]
Chun, Joohwan [1 ]
Song, Sungchan [2 ]
机构：
[1] Korea Adv Inst Sci & Technol, Sch Elect Engn, Daejeon 34141, South Korea
[2] Hanwhasyst Co Ltd, Yongin 449885, South Korea
来源：
2018 IEEE RADAR CONFERENCE (RADARCONF18) | 2018年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A forward-looking scanning radar with a real aperture requires sharp beam width to achieve high cross-range resolution. Also, range resolution is limited by the bandwidth of the transmitted signal. We propose a method for yielding a 2D super-resolution radar image by reweighted l(1)-minimization. Assuming reflectivity distribution of the frontal ground is sparse, - when there only exists dominant scattering points on the ground - imaging problem can be cast to compressive sensing framework so that the super-resolution radar image can be obtained. The super-resolution imaging radar can be adopted as a seeker for the frontal ground surveillance.
引用
收藏
页码：453 / 457
页数：5
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