  This paper presents a complete strategy for the geometry estimation of large
microphone arrays of arbitrary shape. Largeness is intended here in both number
of microphones (hundreds) and size (few meters). Such arrays can be used for
various applications in open or confined spaces like acoustical imaging, source
identification, or speech processing. For so large array systems,measuring the
geometry by hand is impractical. Therefore a blind passive method is proposed.
It is based on the analysis of the background acoustic noise, supposed to be a
diffuse field. The proposed strategy is a two-step process. First the pairwise
microphone distances are identified by matching their measured coherence
function to the one predicted by the diffuse field theory. Second, a robust
multidimensional scaling(MDS) algorithm is adapted and implemented. It takes
advantage of local characteristics to reduce the set of distances and infer the
geometry of the array. This work is an extension of previous studies, and it
overcomes unsolved drawbacks. In particular it deals efficiently with the
outliers known to ruin standard MDS algorithms. Experimental proofs of this
ability are presented by treating the case of two arrays. They show that the
proposed improvements manage large spatial arrays.

Data Analysis, Statistics and Probability