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

• Main Authors: Min-Seok Kang, Kyung-Tae Kim
• Format: Article
• Language: English
• Published: Wiley 2019-09-01
• Series: The Journal of Engineering
• Subjects: image reconstruction; radar imaging; synthetic aperture radar; novel autofocus method; high-resolution inverse synthetic aperture radar image reconstruction; compressive sensing framework; cs reconstruction problem; isar images; tikhonov-regularisation-based algorithm; compressive sensing approach; high-resolution isar image reconstruction
• Online Access: https://digital-library.theiet.org/content/journals/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.