Comparison of conventional and adaptive acoustic beamforming algorithms using a tetrahedral microphone array in noisy environments

In situ acoustic measurements are often plagued by interfering sound sources that occur within the measurement environment. Both adaptive and conventional beamforming algorithms, when applied to the outputs of a microphone array arranged in a tetrahedral geometry, are able to capture sound sources in desired directions and reject sound from unwanted directions. Adaptive algorithms may be able to measure a desired sound source with greater spatial precision, but require more calculations and, therefore, computational power. A conventional frequency-domain phase-shift algorithm and a modified adaptive frequency-domain Minimum Variance Distortionless Response (MVDR) algorithm were applied to simulated and recorded signals from a tetrahedral array of omnidirectional microphones. The algorithms are described mathematically and demonstrated on both deterministic and real-world sound data, to quantitatively validate and compare their performance and to provide listening examples of their outputs in a variety of acoustically replicated environments. Work supported by Portland State University.