Open AccessSAR imaging from incomplete data using elastic net regularisation
Author(s) -
Prünte L.
Publication year - 2017
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.2017.3239
Subject(s) - synthetic aperture radar , computer science , radar imaging , signal to noise ratio (imaging) , noise (video) , elastic net regularization , artificial intelligence , noisy data , missing data , image (mathematics) , net (polyhedron) , computer vision , algorithm , radar , mathematics , telecommunications , machine learning , geometry , feature selection
Synthetic aperture radar imaging suffers significantly from incomplete datasets, where whole pulses are missing. In this Letter, the author introduces an elastic net regularisation to imaging, reducing those artefacts and improving the signal to noise ratio of the image at the same time.