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Phase retrieval with a multivariate Von Mises prior: from a Bayesian formulation to a lifting solution

Abstract

In this paper, we investigate a new method for phase recovery when prior information on the missing phases is available. In particular, we propose to take into account this information in a generic fashion by means of a multivariate Von Mises dis- tribution. Building on a Bayesian formulation (a Maximum A Posteriori estimation), we show that the problem can be expressed using a Mahalanobis distance and be solved by a lifting optimization procedure.Comment: Preprint of the paper published in the proc. of ICASSP'1

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