Compressive sensing approach for high-resolution ISAR image reconstruction and autofocus

• Published in: Journal of engineering (Stevenage, England) Vol. 2019; no. 20; pp. 7017 - 7020
• Main Authors: Kang, Min-Seok, Kim, Kyung-Tae
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.10.2019; Wiley
• Subjects: compressive sensing approach; compressive sensing framework; CS reconstruction problem; high-resolution inverse synthetic aperture radar image reconstruction; high-resolution isar image reconstruction; IET International Radar Conference (IRC 2018); image reconstruction; ISAR images; novel autofocus method; radar imaging; synthetic aperture radar; Tikhonov‐regularisation‐based algorithm; compressive sensing approach; synthetic aperture radar; compressive sensing framework; CS reconstruction problem; ISAR images; high-resolution ISAR image reconstruction; radar imaging; image reconstruction; Tikhonov-regularisation-based algorithm; novel autofocus method; high-resolution inverse synthetic aperture radar image reconstruction
• ISSN: 2051-3305; 2051-3305
• DOI: 10.1049/joe.2019.0572

In this study, a novel autofocus method is presented to achieve high-resolution inverse synthetic aperture radar (ISAR) image reconstruction with limited measurements in the compressive sensing (CS) framework. In order to solve the CS reconstruction problem of ISAR images with sparsity, the CS coupled with Tikhonov-regularisation-based algorithm is devised as an effective focusing technique. The proposed method aims at compensating the phase errors induced by target motions, and can provide globally well-focused ISAR images. Simulation and experimental results verify the effectiveness of the proposed scheme.