Convex approximation to the likelihood criterion for aperture synthesis imaging.
Aperture synthesis allows one to measure visibilities at very high resolutions by coupling telescopes of reasonable diameters. We consider the case where visibility amplitudes and phase are measured separately. It leads to an estimation problem where the noise model yields a nonconvex data-likelihood criterion. We show how to optimally approximate the noise model while keeping the criterion convex. This approximation has been validated both on simulations and on experimental data.
Meimon
Serge
S
Office National d'Etudes et de Recherches Aérospatiales, Département d'Optique Théorique et Appliquée, BP 72, F-92322 Châtillon cedex, France. Serge.Meimon@onera.fr
Mugnier
Laurent M
LM
Le Besnerais
Guy
G
D000465:Algorithms; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007368:Interferometry / Q000379:methods*; D015233:Models, Statistical