Greedy Design of Circular Concentric Arrays for Broadband MVDR

Adaptive beamforming is applied in audio and acoustic applications to enhance a broadband signal of interest while suppressing interferences in challenging acoustic time-varying environments. A significant challenge in designing such beamformers is to minimize the number of sensors while maintaining a required level of performance. Herein, we focus on designing sparse broadband adaptive beamformers for concentric circular arrays, often used in video conferencing and various home vocal applications. We propose an iterative greedy design that selects a small number of sensors distributed over the rings of the array while imposing several constraints regarding the desired attributes of the beamformer. One of the constraints is a joint sparsity constraint on the sensor subset selection. This constraint ensures shared use of all the selected sensors for the bandwidth of interest, contributing to resource consumption reduction. Experimental results demonstrate the benefits of the proposed sparse sensor design in terms of desired signal frequency-invariant recovery and interference suppression level under limited computational and hardware constraints.