• CN：11-2187/TH
• ISSN：0577-6686

• 机械动力学 •

### 基于正交匹配追踪的二维离网压缩波束形成声源识别方法

1. 1. 重庆大学机械传动国家重点实验室 重庆 400044;
2. 重庆大学机械与运载工程学院 重庆 400044;
3. 重庆工业职业技术学院车辆工程学院 重庆 401120
• 收稿日期:2021-06-21 修回日期:2021-12-30 出版日期:2022-06-20 发布日期:2022-08-08
• 通讯作者: 杨洋(通信作者),女,1988年出生,副教授。主要研究方向为噪声源识别技术理论及其应用、阵列信号处理。E-mail:yangyang911127@cqu.edu.com
• 作者简介:杨咏馨,女,1995年出生,博士研究生。主要研究方向为阵列声源识别技术、阵列信号处理。E-mail:yongxinyang@cqu.edu.cn;褚志刚,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
• 基金资助:
国家自然科学基金资助项目（11874096）

### Two-dimensional Off-grid Compressive Beamforming Based on Orthogonal Matching Pursuit for Acoustic Source Identification

YANG Yongxin1,2, CHU Zhigang1,2, YANG Yang2,3

1. 1. State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044;
2. College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044;
3. Faculty of Vehicle Engineering, Chongqing Industry Polytechnic College, Chongqing 401120
• Received:2021-06-21 Revised:2021-12-30 Online:2022-06-20 Published:2022-08-08

Abstract: Two premises need to be satisfied for conventional two-dimensional (2D) on-grid compressive beamforming with a planar microphone array to obtain accurate source identification results. One is that the direction of arrivals (DOAs) of the acoustic source are consistent with the discretized grid points (basis match); the other is that the related prior parameters need to be accurately estimated. However, the above two premises are difficult to meet in practical applications. In this case, the source identification performance of conventional 2D on-grid compressive beamforming will be significantly degraded due to the combined effects of the basis mismatch issue and inaccurate estimation of prior parameters. A 2D off-grid compressive beamforming acoustic source identification method based on orthogonal matching pursuit is proposed to solve this problem. It uses the first-order Taylor expansion of the transfer vector at the grid point to approximate the real transfer vector at the off-grid source, takes the on-grid coordinates, off-grid deviations and strengths of the sources as the unknown parameters to construct the equations, and solves them by orthogonal matching pursuit and least squares method to obtain the off-grid coordinate and strength estimates of the acoustic sources. Both simulations and experiments demonstrate that the proposed method can effectively alleviate the basis mismatch issue, obtain high accuracy of DOAs and source strengths estimation, and achieve better acoustic source identification performance than the conventional on-grid compressive beamforming. It enjoys high computational efficiency. Besides, the proposed method does not require prior knowledge of signal-to-noise ratio and/or regularization parameters and is insensitive to sparsity estimation and the grid spacing, and its acoustic source identification performance is robust.