Frequency-invariant beamformer design via ADPM approach

Junjia Zhang, Pengcheng Gong, Yuntao Wu, Lirong Li, Liang Yu

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

Frequency-invariant (FI) beamformers play an important role in suppressing speech waveform distortions. Due to the perfect FI beampattern (FIB), differential microphone arrays (DMAs) have been widely used in practical applications like voice communication and human-machine interface systems. Superdirective beamforming generated by DMAs have many useful properties but suffer white noise amplification. To address this drawback, we formulate a least squares broadband FI problem, under the white noise output power constraints, to improve robustness of superdirective beamformers. The problem is challenging to solve since FI beamformers are designed on broadband and initialization parameters corresponding to each frequency are different. We devise broadband beampattern synthesis algorithm based on alternating direction penalty method (ADPM), which utilizes the relationship between residuals and penalty terms to reduce the iteration number under the improved framework of alternating direction method of multipliers (ADMM). The proposed ADPM method can decompose the optimization problem into multi-block convex optimization problems and solve them separately. The fast convergence property of our solution is demonstrated via numerical simulations.

源语言英语
文章编号108814
期刊Signal Processing
204
DOI
出版状态已出版 - 3月 2023
已对外发布

指纹

探究 'Frequency-invariant beamformer design via ADPM approach' 的科研主题。它们共同构成独一无二的指纹。

引用此