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Cluster analysis provides a tool for mapping out regions of ambiguous response in sparse array beam forming problems. This paper discusses clustering and its application to matched field processing (MFP) problems in ocean acoustics. The map of the ambiguity volume provided by clustering can be used for improved interpretation and postprocessing. By peak-picking in cluster space, rather than in spatial dimensions, the authors are able to identify and discard ambiguous peaks that result from the presence of a strong source. As shown in a data example, clustering can help collapse three-dimensional MFP output to bearings-only while preserving signal gains obtained by accounting for multipath. Clustering also can provide computational gains by allowing the elimination of highly redundant replicas.