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Radar imaging with compressed sensing
Author(s) -
Harding Brian J.,
Milla Marco
Publication year - 2013
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1002/rds.20063
Subject(s) - compressed sensing , computer science , radar , remote sensing , entropy (arrow of time) , radar imaging , observatory , artificial intelligence , computer vision , algorithm , geology , telecommunications , physics , quantum mechanics , astrophysics
A novel technique for radar‐imaging inversions is proposed which leverages ideas from the emerging field of compressed sensing. This new method takes advantage of the transform sparsity inherent in natural images. Theoretical recovery results are promising and are borne out by simulations in which this technique outperforms Capon's method and the Maximum Entropy method. Preliminary results using data collected at the Jicamarca Radio Observatory are also presented.