Concentric Circular Nested Array Design Method for Acoustic Imaging Based on Differential Coarray Model

Acoustic imaging intuitively illustrates the locations of sound sources and has a wide range of applications, including fault detection. However, this technology requires a substantial number of microphones, which increases the complexity and cost of the data acquisition system. To reduce the number of microphones while maintaining the performance of acoustic imaging, this paper introduces a concentric circular nested array (CCNA) design method. By extending the array using a differential co-array model, a virtual uniform concentric circular array is achieved. This virtual array preserves the advantages of the circular array structure while minimizing the number of required microphones. The performance of the proposed array is validated through simulation experiments. The simulation results demonstrate that the CCNA offers higher resolution, a greater dynamic range (DR), and improved positioning accuracy in acoustic imaging compared to other arrays. Finally, this paper compares the acoustic imaging results of the CCNA with those of the uniform circular array (UCA) through experiments. The experimental results reveal that the positioning accuracy of the proposed CCNA surpasses that of the UCA, thereby confirming the superiority of the proposed design.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-04-03
DOI
https://doi.org/10.1109/jsen.2025.3555811
Citations
1
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
1.49

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article

Concentric Circular Nested Array Design Method for Acoustic Imaging Based on Differential Coarray Model

Zonglong Bai, Wenzhao Zhu, Yan Yang, Junyan Zhang et al.
1 citations
IEEE Sensors Journal
Speech and Audio Processing
1.49
article

Concentric Circular Nested Array Design Method for Acoustic Imaging Based on Differential Coarray Model

Zonglong Bai, Wenzhao Zhu, Yan Yang, Junyan Zhang, Zhiyuan Xie
article en
1 citations

Abstract

Acoustic imaging intuitively illustrates the locations of sound sources and has a wide range of applications, including fault detection. However, this technology requires a substantial number of microphones, which increases the complexity and cost of the data acquisition system. To reduce the number of microphones while maintaining the performance of acoustic imaging, this paper introduces a concentric circular nested array (CCNA) design method. By extending the array using a differential co-array model, a virtual uniform concentric circular array is achieved. This virtual array preserves the advantages of the circular array structure while minimizing the number of required microphones. The performance of the proposed array is validated through simulation experiments. The simulation results demonstrate that the CCNA offers higher resolution, a greater dynamic range (DR), and improved positioning accuracy in acoustic imaging compared to other arrays. Finally, this paper compares the acoustic imaging results of the CCNA with those of the uniform circular array (UCA) through experiments. The experimental results reveal that the positioning accuracy of the proposed CCNA surpasses that of the UCA, thereby confirming the superiority of the proposed design.

IEEE Sensors JournalVol. 25(10)
North China Electric Power University (CN), Yanshan University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hebei Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 21%
Speech and Audio Processing
1.49
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