Low frequency acoustic source imaging method based on coprime position non-synchronous measurement

Juan WEI; Yutao HE; Fangli NING

doi:10.11959/j.issn.1000-436x.2023166

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Low frequency acoustic source imaging method based on coprime position non-synchronous measurement

Papers | 更新时间：2024-06-06

- Low frequency acoustic source imaging method based on coprime position non-synchronous measurement
- Journal on Communications Vol. 44, Issue 9, Pages: 93-103(2023)
- 作者机构：
  
  1. 西安电子科技大学通信工程学院，陕西西安 710071
  2. 西北工业大学机电学院，陕西西安 710072
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(52075441);The Key Research and Development Program of Shannxi Province(2023-YBGY-219);Aeronautical Science Foundation of China(20200015053001);2023 Xi’an Key Industrial Chain Technology Research Project(23ZDCYJSGG0006-2023)
- DOI：10.11959/j.issn.1000-436x.2023166
  CLC： TN912.3
- Online First：2023-09，
  
  Published：25 September 2023
- 稿件说明：
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Juan WEI, Yutao HE, Fangli NING. Low frequency acoustic source imaging method based on coprime position non-synchronous measurement[J]. Journal on Communications, 2023, 44(9): 93-103.
DOI：

Juan WEI, Yutao HE, Fangli NING. Low frequency acoustic source imaging method based on coprime position non-synchronous measurement[J]. Journal on Communications, 2023, 44(9): 93-103. DOI： 10.11959/j.issn.1000-436x.2023166.

摘要

针对声学成像受限于传声器阵列孔径和阵元密度不足，导致在低频、低信噪比条件下声成像分辨率较低的问题，提出一种基于互质位置非同步测量的低频、低信噪比声源高分辨率成像方法。首先，移动原型阵列在互质位置处接收声信号并计算数据缺失的互谱矩阵，然后利用改进的加速近端梯度算法对缺省互谱矩阵进行补全，再对补全后的完整互谱矩阵进行矢量化，最后建立虚拟阵列信号模型并求解。仿真结果表明，在低频、低信噪比条件下，所提方法与以往方法相比，具有更低的定位误差、更高的成像分辨率以及更好的鲁棒性和抗噪性。

Abstract

In order to solve the problem that the acoustic imaging resolution was low under the condition of low frequency and low SNR due to the limited microphone array aperture and element density

a high resolution imaging method of low frequency and low SNR sound source was proposed based on the non-synchronous measurement of the coprime position.Firstly

the acoustic signal was received at the coprime position and the missing cross-spectrum matrix was calculated by the mobile prototype array.Then

the improved accelerated proximity gradient algorithm was used to complete the missing cross-spectrum matrix

and the complete cross-spectrum matrix was vectorized.Finally

the virtual array signal model was established and solved.The simulation results demonstrate that the proposed method has lower positioning error

higher imaging resolution

and better robustness and noise immunity than the previous methods under the condition of low frequency and low SNR.

关键词

Keywords

references

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