  We present a Maximum A Posteriori (MAP) derivation of the Independent Vector
Analysis (IVA) algorithm, a blind source separation algorithm, by incorporating
a prior over the demixing matrices, relying on a free-field model. In this way,
the outer permutation ambiguity of IVA is avoided. The resulting MAP
optimization problem is solved by deriving majorize-minimize update rules to
achieve convergence speed comparable to the well-known auxiliary function IVA
algorithm. The performance of the proposed algorithm is investigated and
compared to a benchmark algorithm using real measurements.
