Open AccessAutofocus approach for sparse aperture inverse synthetic aperture radar imaging
Author(s) -
Xiao Da,
Su Fulin,
Gao Jianjun
Publication year - 2015
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.2015.1516
Subject(s) - autofocus , synthetic aperture radar , computer science , computer vision , inverse synthetic aperture radar , artificial intelligence , iterative reconstruction , compressed sensing , conjugate gradient method , synthetic aperture sonar , radar imaging , image quality , inverse problem , algorithm , radar , mathematics , image (mathematics) , optics , focus (optics) , physics , telecommunications , mathematical analysis
In the inverse synthetic aperture radar imaging, the autofocus is a required step for generating high‐quality images. However, due to many factors, the aperture data may be sparse so that the classical motion compensation approaches and imaging algorithms are not proper. On the basis of the compressed sensing technique and two optimisation methods (the gradient projection method and the conjugate gradient method), a novel autofocus algorithm, which can be used in sparse aperture imaging, is proposed in this Letter. The phase errors induced by the translational Doppler frequency are estimated and the focused image is reconstructed simultaneously by dual iterative computation. This approach is verified by real data processing.