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http://dx.doi.org/10.5515/KJKIEES.2017.28.8.636

Millimeter-Wave(W-Band) Forward-Looking Super-Resolution Radar Imaging via Reweighted ℓ1-Minimization  

Lee, Hyukjung (School of Electrical Engineering, KAIST)
Chun, Joohwan (School of Electrical Engineering, KAIST)
Song, Sungchan (Hanwha Systems)
Publication Information
The Journal of Korean Institute of Electromagnetic Engineering and Science / v.28, no.8, 2017 , pp. 636-645 More about this Journal
Abstract
A scanning radar is exploited widely such as for ground surveillance, disaster rescue, and etc. However, the range resolution is limited by transmitted bandwidth and cross-range resolution is limited by beam width. In this paper, we propose a method for super-resolution radar imaging. If the distribution of reflectivity is sparse, the distribution is called sparse signal. That is, the problem could be formulated as compressive sensing problem. In this paper, 2D super-resolution radar image is generated via reweighted ${\ell}_1-Minimization$. In the simulation results, we compared the images obtained by the proposed method with those of the conventional Orthogonal Matching Pursuit(OMP) and Synthetic Aperture Radar(SAR).
Keywords
Forward-Looking Imaging; Real Beam Scanning Radar; Super-Resolution; Reweighted ${\ell}_1-Minimization$;
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