Open AccessHigh‐resolution SAR imaging from azimuth periodically gapped raw data via generalised orthogonal matching pursuit
Author(s) -
Qian Yulei,
Zhu Daiyin
Publication year - 2018
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2018.5640
Subject(s) - azimuth , synthetic aperture radar , computer science , raw data , point target , artificial intelligence , computer vision , matching pursuit , radar imaging , matching (statistics) , algorithm , remote sensing , radar , optics , compressed sensing , mathematics , physics , geology , telecommunications , statistics , programming language
Occurrence of periodical gapping in synthetic aperture radar (SAR) raw data poses a challenge in obtaining focused images. Traditional SAR imaging algorithms fail to process the periodically gapped raw data. A method is proposed to solve this problem. The presented method consists of phase compensation and recovering raw data in range Doppler domain via generalised orthogonal matching pursuit. Then, the recovered raw data is capable of being processed with the traditional SAR imaging algorithms. The Omega‐K algorithm is selected to focus the reconstructed raw data. The presented method is validated on performing better in comparison with the spectral method periodically gapped amplitude and phase estimation by point target simulation and analysis. In simulation, the raw data loses 50% by the form of azimuth periodical gapping. The resolution of point targets can reach 0.25 m in both azimuth and range direction. In addition, real SAR raw data is utilised to verify the effectiveness of the proposed method.