大连理工大学信息与通信工程学院, 辽宁大连 116024
[ "王 睿 女,1989年生于辽宁省阜新市.现为大连理工大学信息与通信工程学院博士研究生.主要研究方向为阵列信号处理.E‑mail: wangr1989@mail.dlut.edu.cn" ]
[ "陈 喆 男,1975年生于黑龙江省泰来县.现为大连理工大学信息与通信工程学院教授.主要研究方向为音频信号处理、图像处理和宽带无线通信.E‑mail: zhechen@dlut.edu.cn" ]
[ "殷福亮 男,1962年11月生于辽宁省抚顺市.现为大连理工大学信息与通信工程学院教授. 研究方向为音频信号处理、图像处理和宽带无线通信.E‑mail: flyin@dlut.edu.cn" ]
收稿:2020-09-30,
修回:2020-12-17,
纸质出版:2021-12-25
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王睿,陈喆,殷福亮.分布式声传感器阵列校准方法综述[J].电子学报,2021,49(12):2468-2478.
WANG Rui,CHEN Zhe,YIN Fu-liang.Review on Calibration of Distributed Acoustic Sensor Arrays[J].ACTA ELECTRONICA SINICA,2021,49(12):2468-2478.
王睿,陈喆,殷福亮.分布式声传感器阵列校准方法综述[J].电子学报,2021,49(12):2468-2478. DOI: 10.12263/DZXB.20201088.
WANG Rui,CHEN Zhe,YIN Fu-liang.Review on Calibration of Distributed Acoustic Sensor Arrays[J].ACTA ELECTRONICA SINICA,2021,49(12):2468-2478. DOI: 10.12263/DZXB.20201088.
分布式声传感器阵列在军事侦察、公共安全监控和人机交互等领域应用广泛.但时钟异步、频率响应失配和节点位置未知问题严重影响后续基于分布式声传感器阵列的语音处理算法的性能,因此近年来学者们热衷于研究校准这三类阵列失配问题的方法.首先,本文介绍了导致分布式声传感器网络各类失配问题的原因和三类问题解决的先后顺序.然后,将现有的解决三类问题的方法进行了综述.其中,时钟同步方法主要包括基于时间戳交换和短时傅里叶变换域线性相位漂移的方法,频率响应校准方法主要包括基于声源导向矢量和自适应滤波器的方法,节点位置/位姿校准方法则主要包括基于节点间几何构型和深度学习的方法.最后,给出了本领域未来研究的方向.
Distributed acoustic sensor arrays have been widely employed in many applications
such as military reconnaissance
security monitoring
man-machine interaction
etc. However
the problems of clock asynchrony
frequency response mismatch and unknown node location seriously affect the performance of subsequent speech processing algorithms based on distributed acoustic sensor arrays. Therefore
scholars have been keen to study calibration methods for these three problems in recent years. This article first introduces the causes of these mismatch problems and the sequence of solving the three problems. Then
the existing methods for these three problems are reviewed. Specifically
clock synchronization methods mainly include methods based on timestamp exchange and linear phase shift in short‑time Fourier transform domain
frequency response calibration methods mainly include methods based on steering vector of sound source and adaptive filter
and node position/pose calibration methods mainly include methods based on geometric configuration among nodes and deep learning. Finally
the future research directions are provided.
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