Fundamental Approaches to Robust Differential Beamforming With High Directivity Factors

Huang G, Benesty J, Chen J (2022)


Publication Type: Journal article

Publication year: 2022

Journal

Pages Range: 1-15

DOI: 10.1109/TASLP.2022.3209935

Abstract

Differential beamforming, which measures the spatial derivatives of the acoustic pressure field, can be used in a wide range of small devices that require high-fidelity sound and speech acquisition as it can achieve frequency-invariant spatial responses with high directivity factors (DFs). Since a differential process is inherently sensitive to sensors' self noise and other array imperfections, the most challenging problem in the design of any differential beamformer is how to achieve the maximum possible DF while maintaining a proper level of robustness for practical usage. While significant efforts have been made on this topic, the problem remains unsolved and further study is indispensable. This paper is devoted to dealing with this challenging problem. It presents a study on theory and methods to achieve the optimal and fundamental compromise between the white noise gain (WNG), which quantifies how robust is the beamformer, and the DF in differential beamforming. The major contributions of this work are as follows. 1) We show and prove that any null constrained fixed beamformer can be decomposed as the sum of two orthogonal filters, i.e., the maximum WNG (MWNG) beamformer and a reduced-rank one. Based on this decomposition, we develop three kinds of differential beamformers from the WNG perspective, which can achieve a flexible and optimal compromise between DF and WNG. 2) We show that a transformed null constrained beamformer can also be decomposed as the sum of two orthogonal filters, i.e., the transformed maximum DF (MDF) beamformer and another reduced-rank one. Based on this decomposition, we also develop three kinds of differential beamformers, which can obtain the desired level of DF while using the rest of the degrees of freedom to maximize the WNG. Simulations are performed to validate the theoretical analysis and developed differential beamformers.

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APA:

Huang, G., Benesty, J., & Chen, J. (2022). Fundamental Approaches to Robust Differential Beamforming With High Directivity Factors. IEEE/ACM Transactions on Audio, Speech and Language Processing, 1-15. https://dx.doi.org/10.1109/TASLP.2022.3209935

MLA:

Huang, Gongping, Jacob Benesty, and Jingdong Chen. "Fundamental Approaches to Robust Differential Beamforming With High Directivity Factors." IEEE/ACM Transactions on Audio, Speech and Language Processing (2022): 1-15.

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