Array Designs Optimized for Both Low-Frequency NAH and High-Frequency Beamforming

Hald, J\atrgen; Gade, Svend

doi:10.4271/2005-08-0014

Cited by 7 publications

(4 citation statements)

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“…The geometry has been optimized for minimum sidelobe level with DAS beamforming measurements up to 6 kHz as described in Ref. 4. This optimization guarantees a maximum ability of the array to distinguish plane waves incident from different directions.…”

Section: Array Designmentioning

confidence: 99%

“…Some patch NAH methods, for example, the equivalent source method (ESM) 1 and statistically optimized near-field acoustical holography (SONAH), 2,3 can work with irregular microphone array geometries, but still require an average array-element spacing less than half the wavelength. As described by Hald,4 this allows the use of irregular arrays that are actually designed for use with beamforming. Typically, good performance with beamforming can be achieved up to frequencies where the average array interelement spacing is 2-3 wavelengths.…”

Section: Introductionmentioning

confidence: 99%

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Fast wideband acoustical holography

Hald

2016

The Journal of the Acoustical Society of America

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Patch near-field acoustical holography methods like statistically optimized near-field acoustical holography and equivalent source method are limited to relatively low frequencies, where the average array-element spacing is less than half of the acoustic wavelength, while beamforming provides useful resolution only at medium-to-high frequencies. With adequate array design, both methods can be used with the same array. But for holography to provide good low-frequency resolution, a small measurement distance is needed, whereas beamforming requires a larger distance to limit sidelobe issues. The wideband holography method of the present paper was developed to overcome that practical conflict. Only a single measurement is needed at a relatively short distance and a single result is obtained covering the full frequency range. The method uses the principles of compressed sensing: A sparse sound field representation is assumed with a chosen set of basis functions, a measurement is taken with an irregular array, and the inverse problem is solved with a method that enforces sparsity in the coefficient vector. Instead of using regularization based on the 1-norm of the coefficient vector, an iterative solution procedure is used that promotes sparsity. The iterative method is shown to provide very similar results in most cases and to be computationally much more efficient.

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Section: Array Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fast wideband acoustical holography

Hald

2016

The Journal of the Acoustical Society of America

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“…The improved algorithms significantly enhance the spatial resolution and remove the interference side-lobes by deconvolution of the array point spread function [14]. Since typically the focusing capabilities of beamforming methods require that all array microphones be exposed almost equally to any monopole on the source plane, the measurement distance between microphones and focusing points is usually required to be not smaller than the array diameter to keep the side-lobes at low levels [15]. As a consequence, the resolution of beamforming methods is limited to around one wavelength by Rayleigh criterion, which is poor at low frequencies.…”

Section: Introductionmentioning

confidence: 99%

Sub-wavelength focusing for low-frequency sound sources using an iterative time reversal method

Li¹,

Li²,

Pan³

et al. 2022

Meas. Sci. Technol.

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Microphone array measurement processed with the image algorithm is commonly performed to identify and quantify noise sources of machines, which is the premise of noise control. However, due to the limitation of the half-wavelength theory, Beamforming and Time Reversal (TR) methods are difficult to separate multiple low-frequency sources. Although near-field acoustic holography can overcome the diffraction limit, it will encounter the ill-posed problem. To avoid solving the inverse problem, iterative time reversal processing (Iterative-TR) is proposed to obtain the sub-wavelength focusing and improve the spatial resolution at low-frequency. The focusing result is corrected step by step with iteration implemented until the result reaches the convergence threshold. The propagation matrix between microphones and focusing points is reconstructed by singular-value normalization to ensure the convergence of the iteration. Numerical simulation results show that Iterative-TR method is able to break through diffraction limit below 1000 Hz within a measurement distance of 0.5 m and reach convergence within 105 iterations that is less than 10 s. The experimental results in indoors with significant reverberation show that Iterative-TR has the ability to stably give the multiple source positions with 0.11 m spacing even at 100 Hz, that is, the spatial resolution reaches 1/31 wavelength. Detailed analysis shows that the overall performance of Iterative-TR outperforms other methods capable of subwavelength focusing for signals below 1000 Hz. The identification of two loudspeakers in the car shows the practicality of the proposed method.

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“…The main disadvantage of beamforming is the poor spatial resolution particularly at low frequencies. Additionally beamforming map is also suffers from the appearance of ghost sources due to side-lobe effects [3,4].…”

Section: Introductionmentioning

confidence: 99%

Improving the efficiency of DAMAS for sound source localization via wavelet compression computational grid

Liu²

2017

Journal of Sound and Vibration

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Phased microphone arrays are used widely in the applications for acoustic source localization. Deconvolution approaches such as DAMAS successfully overcome the spatial resolution limit of the conventional delay-and-sum (DAS) beamforming method. However deconvolution approaches require high computational effort compared to conventional DAS beamforming method. This paper presents a novel method that serves to improve the efficiency of DAMAS via wavelet compression computational grid rather than via optimizing DAMAS algorithm. In this method, the efficiency of DAMAS increases with compression ratio. This method can thus save lots of run time in industrial applications for sound source localization, particularly when sound sources are just located in a small extent compared with scanning plane and a band of angular frequency needs to be calculated. In addition, this method largely retains the spatial resolution of DAMAS on original computational grid, although with a minor deficiency that the occurrence probability of aliasing increasing slightly for complicated sound source.

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Array Designs Optimized for Both Low-Frequency NAH and High-Frequency Beamforming

Cited by 7 publications

References 0 publications

Fast wideband acoustical holography

Fast wideband acoustical holography

Sub-wavelength focusing for low-frequency sound sources using an iterative time reversal method

Improving the efficiency of DAMAS for sound source localization via wavelet compression computational grid

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