Fast Fourier-based deconvolution for three-dimensional acoustic source identification with solid spherical arrays

Yang, Yang; Chu, Zhigang; Shen, Linbang; Ping, Guoli; Xu, Zhongming

doi:10.1016/j.ymssp.2018.01.028

Cited by 11 publications

(3 citation statements)

References 33 publications

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“…SHB is computationally efficient; however, it suffers from poor spatial resolution and severe sidelobe contamination [6]. To improve the acoustic source identification performance of beamforming with spherical microphone arrays, filter and sum (FAS) [7], deconvolution [8,9], and functional delay and sum (FDAS) [10,11] are successively proposed. FAS shows computational efficiency comparable to SHB and stronger sidelobe suppression than SHB, but it does not show improved spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Performance Enhancement of Functional Delay and Sum Beamforming for Spherical Microphone Arrays

Zhao

Chu

2022

Electronics

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Functional delay and sum (FDAS) beamforming for spherical microphone arrays can achieve 360° panoramic acoustic source identification, thus having broad application prospects for identifying interior noise sources. However, its acoustic imaging suffers from severe sidelobe contamination under a low signal-to-noise ratio (SNR), which deteriorates the sound source identification performance. In order to overcome this issue, the cross-spectral matrix (CSM) of the measured sound pressure signal is reconstructed with diagonal reconstruction (DRec), robust principal component analysis (RPCA), and probabilistic factor analysis (PFA). Correspondingly, three enhanced FDAS methods, namely EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA, are established. Simulations show that the three methods can significantly enhance the sound source identification performance of FDAS under low SNRs. Compared with FDAS at SNR = 0 dB and the number of snapshots = 1000, the average maximum sidelobe levels of EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA are reduced by 6.4 dB, 21.6 dB, and 53.1 dB, respectively, and the mainlobes of sound sources are shrunk by 43.5%, 69.0%, and 80.0%, respectively. Moreover, when the number of snapshots is sufficient, the three EFDAS methods can improve both the quantification accuracy and the weak source localization capability. Among the three EFDAS methods, EFDAS-DRec has the highest quantification accuracy, and EFDAS-PFA has the best localization ability for weak sources. The effectiveness of the established methods and the correctness of the simulation conclusions are verified by the acoustic source identification experiment in an ordinary room, and the findings provide a more advanced test and analysis tool for noise source identification in low-SNR cabin environments.

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Section: Introductionmentioning

confidence: 99%

Performance Enhancement of Functional Delay and Sum Beamforming for Spherical Microphone Arrays

Zhao

Chu

2022

Electronics

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“…Ning 35 proposed the use of compressed sensing in three-dimensional localization. Chu [36][37][38][39][40] and Koutny 41 studied the three-dimensional deconvolution method based on the spherical array and compared the localization effect of various methods. Wang 42 proposed expectation-maximization (EM) and Evidential EM (E2M) algorithm to estimate multiple sound sources in a statistical framework by maximum likelihood.…”

Section: Introductionmentioning

confidence: 99%

A fast 3D-MUSIC method for near-field sound source localization based on the bat algorithm

Yang

Sun

Guo

et al. 2022

International Journal of Aeroacoustics

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To improve the computation and real-time performances of the multiple signal classification (MUSIC) algorithm in 3D space, a fast sound source localization method based on the bat algorithm (BA) and the 3D-MUSIC, called BA-based 3D-MUSIC algorithm (3D-BMUSIC), is presented in this paper. 3D-BMUSIC greatly reduces the computation load by replacing the regular grid search with the BA. First, the near-field spherical wave model is established to obtain the spectral function of the 3D-MUSIC. Then, the spectral function is defined as the fitness function, which calculates the fitness value corresponding to each bat position. Finally, the global optimal bat position with the largest fitness value, as sound source localization, is obtained by successive iteration and sorting. The simulation and experiment show that 3D-BMUSIC accurately estimates the DOA and distance of near-field sources, and the root-mean-square error (RMSE) of 3D-BMUSIC is less than that of 3D-MUSIC. In addition, 3D-BMUSIC effectively reduces the computation time by approximately 96–98%. With shorter computation time and higher efficiency, 3D-BMUSIC promotes hardware implementation and is more suitable for high-precision localization of near-field sound sources.

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“…Noise control is an important research work in the fields of automobiles, [1][2] aero-engines, [3][4][5] high-speed rail, [6][7] propeller plane, [8][9] and other fields. How to accurately identify noise sources is the premise and foundation of noise control.…”

Section: Introductionmentioning

confidence: 99%

Improvement of orthogonal matching pursuit deconvolution beamforming method for acoustic source identification

Zhang¹,

Wen²,

Yan

et al. 2022

Journal of Low Frequency Noise, Vibration and Active Control

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The deconvolution approach for the mapping of acoustic sources (DAMAS) based on orthogonal matching pursuit (OMP-DAMAS) has attracted much attention due to its advantages of high spatial resolution and excellent capability to suppress spurious sources. In this paper, we propose an improved version of OMP-DAMAS based on fast Fourier transformation (FFT), abbreviated as FFT-OMP-DAMAS. This method assumes that the array point spread functions (PSFs) are spatially shift-invariant. The sum of the product of the acoustic source distribution and PSFs is converted into a convolution form, which is further converted into a product in the wave number domain. With these conversions, FFT can be used to improve the solving speed. Both simulations and experiments show that the proposed method not only inherits the advantages of OMP-DAMAS in terms of spatial resolution and spurious source suppression but also significantly improves the computational efficiency compared with OMP-DAMAS.

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Fast Fourier-based deconvolution for three-dimensional acoustic source identification with solid spherical arrays

Cited by 11 publications

References 33 publications

Performance Enhancement of Functional Delay and Sum Beamforming for Spherical Microphone Arrays

Performance Enhancement of Functional Delay and Sum Beamforming for Spherical Microphone Arrays

A fast 3D-MUSIC method for near-field sound source localization based on the bat algorithm

Improvement of orthogonal matching pursuit deconvolution beamforming method for acoustic source identification

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