Improved SAR imaging algorithm with azimuth periodically missing data

• Published in: IET radar, sonar & navigation Vol. 14; no. 3; pp. 399 - 406
• Main Authors: Yang, Weixing, Bi, Hui, Zhu, Daiyin
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.03.2020
• Subjects: aliasing; approximate observation model; azimuth missing data; compressed sensing; compressed sensing theory; computational complexity; data processing; ghosting; image reconstruction; imaging quality; iterative methods; iterative shrinkage thresholding algorithm; Lp‐alternating direction method; memory consumption; radar imaging; rapid reconstruction imaging; Research Article; SAR azimuth; SAR imaging algorithm; SAR raw data; synthetic aperture radar; iterative methods; compressed sensing; memory consumption; ghosting; data processing; Lp-alternating direction method; image reconstruction; iterative shrinkage thresholding algorithm; compressed sensing theory; SAR imaging algorithm; imaging quality; synthetic aperture radar; azimuth missing data; SAR azimuth; rapid reconstruction imaging; radar imaging; approximate observation model; SAR raw data; aliasing; computational complexity
• ISSN: 1751-8784; 1751-8792; 1751-8792
• DOI: 10.1049/iet-rsn.2019.0320

Aiming at the periodically missing data of synthetic aperture radar (SAR) in azimuth, a reconstruction and imaging algorithm based on ${\bi L}_p$Lp-alternating direction method with compressed sensing theory is proposed. The algorithm can effectively suppress ghosting and aliasing caused by azimuth missing data, and improve the imaging quality. To reduce memory consumption and lower computational complexity, approximate observation model based on SAR raw data simulator is utilised to rapid reconstruction imaging. Compared to the traditional iterative shrinkage thresholding algorithm, the proposed algorithm has better reconstruction image quality. Simulation and raw SAR echo data processing demonstrate the effectiveness of the proposed method in solving the problem of imaging with periodically missing data in SAR azimuth.