Performance analysis of microphone array methods

Microphone array methods aim at the characterization of multiple simultaneously operating sound sources. However, existing data processing algorithms have been shown to yield different results when applied to the same input data. The present paper introduces a method for estimating the reliability of such algorithms. Using Monte Carlo simulations, data sets with random variation of selected parameters are generated. Four different microphone array methods are applied to analyze the simulated data sets. The calculated results are compared with the expected outcome, and the dependency of the reliability on several parameters is quantified. It is shown not only that the performance of a method depends on the given source distribution, but also that the methods differ in terms of their sensitivity to imperfect input data.