Sparse Distortionless Beamformer Based on Nonconvex Optimization

Taiga Kawamura, Kohei Yatabe, Ryoichi Miyazaki

研究成果: Conference contribution

抄録

Minimum power distortionless response (MPDR) beamformer is a popular beamformer that minimizes its output power under the distortionless constraint. To improve the performance of the MPDR beamformer, a sparse distortionless beamformer has been proposed. It minimizes the ℓ1 norm of the output signal under the same constraint so that the output has sparse time-frequency representation. While the ℓ1-norm-based formulation is theoretically advantageous owing to its convexity, its practical performance might not be excellent because of the bias of the ℓ1 norm. To reduce the bias and improve the performance, we propose a sparse distortionless beamformer based on a nonconvex sparsity-inducing objective function. The proposed beamformer is performed via a heuristic application of a primal-dual splitting algorithm. The experiments showed that the proposed beamformer can achieve higher performance and is more robust against mismatch of the target direction.

本文言語English
ホスト出版物のタイトル29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings
出版社European Signal Processing Conference, EUSIPCO
ページ281-285
ページ数5
ISBN(電子版)9789082797060
DOI
出版ステータスPublished - 2021
イベント29th European Signal Processing Conference, EUSIPCO 2021 - Dublin, Ireland
継続期間: 2021 8月 232021 8月 27

出版物シリーズ

名前European Signal Processing Conference
2021-August
ISSN(印刷版)2219-5491

Conference

Conference29th European Signal Processing Conference, EUSIPCO 2021
国/地域Ireland
CityDublin
Period21/8/2321/8/27

ASJC Scopus subject areas

  • 信号処理
  • 電子工学および電気工学

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