• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2021, Vol. 57 ›› Issue (24): 166-183.doi: 10.3901/JME.2021.24.166

• 仪器科学与技术 • 上一篇    下一篇

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高性能波束形成声源识别方法研究综述

杨洋1,2, 褚志刚1   

  1. 1. 重庆大学机械与运载工程学院 重庆 400044;
    2. 重庆工业职业技术学院车辆工程学院 重庆 401120
  • 收稿日期:2021-03-11 修回日期:2021-09-02 出版日期:2021-12-20 发布日期:2022-02-28
  • 通讯作者: 褚志刚(通信作者),男,1978年出生,博士,教授,博士研究生导师。主要研究方向为振动噪声测量分析技术、噪声源识别技术理论及其应用、工程信号处理。E-mail:zgchu@cqu.edu.cn
  • 作者简介:杨洋,女,1988年出生,博士研究生。主要研究方向为噪声源识别技术理论及其应用、工程信号处理。E-mail:yangyang911127@cqu.edu.com
  • 基金资助:
    国家自然科学基金(11874096,11704040)和重庆市自然科学基金(cstc2019jcyj-msxmX0399)资助项目。

A Review of High-performance Beamforming Methods for Acoustic Source Identification

YANG Yang1,2, CHU Zhigang1   

  1. 1. College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044;
    2. Faculty of Vehicle Engineering, Chongqing Industry Polytechnic College, Chongqing 401120
  • Received:2021-03-11 Revised:2021-09-02 Online:2021-12-20 Published:2022-02-28

摘要: 基于传声器阵列测量的波束形成声源识别技术广泛应用于军事、工业、环境等领域。围绕“空间分辨能力增强、寄生虚假声源抑制、定位定量精度提升、鲁棒稳健性能强化、声源识别功能完善”的目标,国内外学者开展了大量研究工作并取得了丰硕成果,反卷积波束形成、函数型波束形成和压缩波束形成三类典型高性能方法先后被提出。为帮助国内学者全面了解三类高性能波束形成方法并加以推广应用,系统阐述其核心思想,全面综述其重要研究进展,根据需要计算的阵列点传播函数的数目对反卷积波束形成进行科学分类,根据采用的网格点类型对压缩波束形成进行科学分类。综述同时涵盖适宜识别阵列前方局部区域内声源的平面传声器阵列和适宜360°全景识别声源的球面传声器阵列。

关键词: 声源识别, 反卷积波束形成, 函数型波束形成, 压缩波束形成, 平面传声器阵列, 球面传声器阵列

Abstract: Beamforming acoustic source identification technology based on microphone array measurements is widely used in military, industrial, environmental and other fields. For the goals of enhancing spatial resolution capability, suppressing parasitic false sources, improving localization and quantification accuracy, strengthening robustness, and perfecting identification function, a lot of researches have been conducted and fruitful achievements have been obtained. Three categories of state-of-the-art high-performance methods, including deconvolution beamforming, functional beamforming and compressive beamforming, are proposed successively. To help domestic scholars comprehensively understand and popularize these methods, their core ideas are systematically expounded and important research progresses are comprehensively reviewed. Deconvolution beamforming methods are scientifically classified according to the number of array point spread functions to be calculated. Compressive beamforming methods are scientifically classified according to the type of grid points to be used. Both planar and spherical microphone arrays are covered. The former is suitable for identifying acoustic sources in a local region in front of the array, and the latter is suitable for 360° panoramically identifying acoustic sources.

Key words: acoustic source identification, deconvolution beamforming, functional beamforming, compressive beamforming, planar microphone array, spherical microphone array

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