Motion-Tolerant Beamforming with Deformable Microphone Arrays
This addresses beamforming for wearable devices with moving microphones, but it is incremental as it adapts existing methods to a specific deformation context.
The paper tackles beamforming for deformable microphone arrays, where sensors move relative to each other, by comparing geometry-tracking and time-invariant approaches, showing the latter works well for small motions relative to acoustic wavelengths in a wearable scenario.
Microphone arrays are usually assumed to have rigid geometries: the microphones may move with respect to the sound field but remain fixed relative to each other. However, many useful arrays, such as those in wearable devices, have sensors that can move relative to each other. We compare two approaches to beamforming with deformable microphone arrays: first, by explicitly tracking the geometry of the array as it changes over time, and second, by designing a time-invariant beamformer based on the second-order statistics of the moving array. The time-invariant approach is shown to be appropriate when the motion of the array is small relative to the acoustic wavelengths of interest. The performance of the proposed beamforming system is demonstrated using a wearable microphone array on a moving human listener in a cocktail-party scenario.