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In this article we analyze the state-of-the-art in multilateration - thefamily of localization methods enabled by the range difference observations.These methods are computationally efficient, signal-independent, and flexiblewith regards to the number of sensing nodes and their spatial arrangement.However, the multilateration problem does not admit a closed-form solution inthe general case, and the localization performance is conditioned on theaccuracy of range difference estimates. For that reason, we consider asimplified use case where multiple distributed microphones capture the signalcoming from a near field sound source, and discuss their robustness to theestimation errors. In addition to surveying the relevant bibliography, wepresent the results of a small-scale benchmark of few "mainstream"multilateration algorithms, based on an in-house Room Impulse Response dataset.

A Comparative Study of Multilateration Methods for Single-Source Localization in Distributed Audio