title: Convex approximation to the likelihood criterion for aperture synthesis imaging.
abstract: 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.
authors.affiliation: 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
authors.forename: Serge
authors.initials: S
authors.lastname: Meimon
authors.forename: Laurent M
authors.initials: LM
authors.lastname: Mugnier
authors.forename: Guy
authors.initials: G
authors.lastname: Le Besnerais
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007368:Interferometry / Q000379:methods*; D015233:Models, Statistical