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

Spatially Informed Independent Vector Analysis