Page 145 - 应用声学2019年第4期

第 38 卷 第 4 期 Vol. 38, No. 4
2019 年 7 月 Journal of Applied Acoustics July, 2019

⋄ 李启虎院士八十华诞学术论文 ⋄

分布式压缩感知麦克风阵列多声源方位估计 ∗

黄惠祥 郭秋涵 童 峰 † 吴燕艺

(厦门大学 水声通信与海洋信息技术教育部重点实验室 厦门 361100)
摘要 麦克风阵列已被广泛应用于音/视频会议等人机交互领域中，多声源应用场景对声源方位估计性能提
出了更高的要求。压缩感知声源定位算法将声源定位问题转化为信号的稀疏重构问题，相比传统的定位算法
如联合可控响应功率和相位变换和时延累加定位能够获得较高的定位性能，但多声源的存在一定程度上降低
了稀疏程度，影响了压缩感知重构性能。考虑到传统的压缩感知定位算法并未利用多个连续语音帧之间声源
空间向量的共同稀疏性，提出采用分布式压缩感知理论以改善多声源的稀疏恢复估计的性能。仿真和实验结
果表明，相比于传统定位算法和压缩感知 -正交匹配追踪算法，分布式压缩感知 -同步正交匹配追踪算法在不
同信噪比和不同声源强度的环境中，对多声源的方位估计都具有更好的定位性能和定位稳健性。
关键词 麦克风阵列，多声源定位，分布式压缩感知
中图法分类号: TN912.3 文献标识码: A 文章编号: 1000-310X(2019)04-0605-10
DOI: 10.11684/j.issn.1000-310X.2019.04.018

Distributed compressed sensing microphone array multi-source
azimuth estimation

HUANG Huixiang GUO Qiuhan TONG Feng WU Yanyi

(Key Laboratory of Underwater Acoustic Communication and Marine Information Technology Ministry of Education,
Xiamen University, Xiamen 361100, China)

Abstract Microphone arrays have been widely used in the field of human-computer interaction such as
audio/video conferencing. It is necessary to make higher-resolution azimuth estimation performance for scenes
with multiple sound sources in different orientations. The compressed sensing (CS) sound source localization
algorithm transforms the sound source localization problem into a sparse reconstruction problem of the signal,
thus achieves better estimation performance compared to traditional localization algorithms such as steered
response power with the phase transform (SRP-PHAT) and time delay-sum (DS). However, the existence of
multiple sound sources reduces the sparsity, to some extent degrades the performance of CS reconstruction.
Considering that the traditional CS localization algorithm does not utilize the common sparsity of the sound
source space vector between multiple consecutive speech frames, in this paper the distributed compressed
sensing (DCS) theory is proposed to improve the performance of sparse recovery estimation of multiple sound
sources. The simulation and experimental results show that compared with traditional positioning algorithm
and compressed sensing-orthogonal matching pursuit (CS-OMP) algorithm, distributed compressed sensing-
simultaneous orthogonal matching pursuit (DCS-SOMP) algorithm has better positioning performance and
robustness for multi-sound source azimuth estimation under different SNR and different sound source intensity
environments.
Key words Microphone array, Multi-source positioning, Distributed compressed sensing

2019-01-21 收稿; 2019-04-05 定稿
国家自然科学基金项目 (11574258), 福建省高校产学合作项目 (2015H6019), 中央高校基本科研业务费专项资金项目 (20720190102)
∗
作者简介: 黄惠祥 (1993- ), 男, 福建泉州人, 硕士研究生, 研究方向: 麦克风阵列信号处理。
† 通讯作者 E-mail: ftong@xmu.edu.cn