Rotating and stationary sound sources separation method based on MCB

Abstract

Traditional beamforming methods do not effectively separate the mixed field of sound sources for different rotational speeds. The coexistence of these sources often manifests out-of-focus sources (for instance, stationary sources appearing with a rotational focus), thereby blurring the beamforming outcomes. Most existing algorithms for segregating rotational different speed sources employ a virtual rotating array utilizing ring arrays. However, due to the constant microphone spacing, the acoustic imaging of the ring array suffers from the interference of high-level side lobes. In this work, a hybrid deconvolution method based on modal composition beamforming is used to explore the ability of a multi-arm spiral array to separate different speed sources. Considering the even energy distribution from the out-of-focus source along the circular trajectory, the beamforming result of out-of-focus sources exhibits a weaker amplitude than the source amplitude. Therefore, out-of-focus sources can be considered noise. First, the point spread function is derived based on the modal transfer function. Then, a system of linear equations is constructed based on an incomplete cross-point spread function matrix. Finally, the source separation is solved through sparse-constrained deconvolution. Simulation and experimental results demonstrate that this method can accurately locate and separate different rotational speed sound sources.