Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace

ZHOU Jing; BAO Chang-chun; ZHANG Xu

doi:10.12263/DZXB.20220210

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Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace

PAPERS | 更新时间：2025-07-02

- Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace
- ACTA ELECTRONICA SINICA Vol. 51, Issue 1, Pages: 76-85(2023)
- 作者机构：
  
  北京工业大学信息学部语音与音频信号处理实验室，北京 100124
- 作者简介：
- 基金信息：
  
  Foundation Item(s):　National Natural Science Foundation of China(61831019)
- DOI：10.12263/DZXB.20220210
  CLC： TN912
- Received：01 March 2022，
  
  Revised：2022-10-03，
  
  Published：25 January 2023
- 稿件说明：
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周静,鲍长春,张旭.基于聚焦信号子空间估计导向矢量的干扰声源抑制方法[J].电子学报,2023,51(01):76-85.

ZHOU Jing,BAO Chang-chun,ZHANG Xu.Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace[J].ACTA ELECTRONICA SINICA,2023,51(01):76-85.
周静,鲍长春,张旭.基于聚焦信号子空间估计导向矢量的干扰声源抑制方法[J].电子学报,2023,51(01):76-85. DOI： 10.12263/DZXB.20220210.

ZHOU Jing,BAO Chang-chun,ZHANG Xu.Suppression Method of the Interference Sound Sources by Estimated Steering Vector Based on the Focusing Signal Subspace[J].ACTA ELECTRONICA SINICA,2023,51(01):76-85. DOI： 10.12263/DZXB.20220210.

摘要

针对最小方差无失真响应（Minimum Variance Distortionless Response

MVDR）波束形成器对导向矢量失配较敏感的问题，本文提出了一种有效的干扰声源抑制方法.该方法首先将语音信号的频带划分为多个子带，通过聚焦信号子空间方法估计各子带的声源到达方向（Direction of Arrival

DOA），并采用统计直方图估计各声源的初始DOA；其次，为了减小导向矢量失配，利用声源的空间稀疏性，通过Capon功率构建目标声源导向矢量估计的代价函数，约束目标声源导向矢量远离干扰声源空间；最后，根据估计的导向矢量，估计干扰声源加噪声协方差矩阵，以获得MVDR波束形成器的权重.基于TIMIT语料库的实验结果证明，提出的干扰声源抑制方法的输出信干噪比（SINR）及语音质量感知评价（PESQ）优于参考方法，具有更佳的抗导向矢量失配性能.

Abstract

Based on the problem that the minimum variance distortionless response (MVDR) beamformer is very sensitive to the mismatch of the steering vector

an effective method of suppressing the interference sound sources is proposed in this paper. First

the bandwidth of speech signal is divided into multiple sub-bands

and the direction of arrival (DOA) of sound sources at each sub-band is estimated by the focusing signal subspace method. Specially

the initial DOA of each sound source is estimated via statistical histogram. Second

in order to reduce the mismatch of the steering vector

based on the spatial sparsity of sound sources

the cost function used for the steering vector estimation of the target sound source is constructed by Capon power so that the steering vector of the target sound source is constrained away from the space of interference sound sources. Finally

the covariance matrix of interference sound source plus noise is estimated based on the estimated steering vector for obtaining the weights of the MVDR beamformer. The experimental results on the TIMIT corpus show that the proposed method outperforms the reference methods on the tests of the output signal to interference-plus-noise ratio (SINR) and the perceptual evaluation of speech quality (PESQ) and has a better performance for preventing the mismatch of the steering vector.

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references

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