Three-dimensional beamforming of dipolar aeroacoustic sources

Porteous, Ric; Prime, Zebb; Doolan, Con J.; Moreau, Danielle; Valeau, Vincent

doi:10.1016/j.jsv.2015.06.030

Cited by 71 publications

(14 citation statements)

References 25 publications

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“…Ultimately, the mutual cancellation is achieved by computing respectively and multiplying together. The proposed method successfully improved the resolution of 3D beamforming with less sensors compared with arrays of [16,17].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Improved algorithm of three-dimensional beamforming based on spatial cross-array

Song¹,

Xu²,

Shu³

et al. 2016

J. vibroeng.

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Three-dimensional beamforming based on microphone array signal processing is the expansion of traditional 2D beamforming. However, its identification accuracy is often badly reduced by the effect of grating lobes and side lobes. To overcome this problem, a method called the hybrid method beamforming (HMB) combining functional generalized inverse beamforming with multiplicative filter of spatial cross-array is proposed. In this method, the statistically optimal processing and iterated generalized inverse beamforming with regularized matrix function are utilized to obtain initial result. Then the high order function is applied to filter the output. Subsequently, a novel non-uniform spatial cross-array optimized by genetic algorithm is used to obtain sound pressure distribution. The array consists of three orthogonal sub-arrays. Mutual cancellation is realized by computing respectively with data of sub-arrays and multiplying together. With fewer microphones, the result of the improved method can be obtained with a higher spatial resolution. The proposed method is verified by the simulation and the source localization test in a room. Compared with the conventional frequency domain beamforming (FDBF) algorithm and statistically optimal array processing (SOAP) beamforming, the performance of the proposed method is significantly improved in terms of resolution of the acoustic source.

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Section: Discussionmentioning

confidence: 99%

“…However, its application is obviously limited by the needs of huge number of sensors. After simplifying the array geometry, Ric Porteous [17] proposed arrangement of two orthogonal planar spiral arrays. Four kinds of three-dimensional beamformers were compared.…”

Section: Introductionmentioning

confidence: 99%

Improved algorithm of three-dimensional beamforming based on spatial cross-array

Song¹,

Xu²,

Shu³

et al. 2016

J. vibroeng.

View full text Add to dashboard Cite

show abstract

“…In their approach, a DSBF method with many two-dimensional (2D) planes was used to estimate an accurate source position in 3D space. Porteous et al proposed a 3D position estimation technique by applying a dual position-based beamforming technique without using the candidate 2D planes [17]. However, their approach demanded a large number of microphones, making the system complicated for use in sports simulation.…”

Section: Introductionmentioning

confidence: 99%

Screen-Based Sports Simulation Using Acoustic Source Localization

et al. 2019

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In this paper, we introduce a novel acoustic source localization in a three-dimensional (3D) space, based on a direction estimation technique. Assuming an acoustic source at a distance from adjacent microphones, its waves spread in a planar form called a planar wavefront. In our system, the directions and steering angles between the acoustic source and the microphone array are estimated based on a planar wavefront model using a delay and sum beamforming (DSBF) system and an array of two-dimensional (2D) microelectromechanical system (MEMS) microphones. The proposed system is designed with parallel processing hardware for real-time performance and implemented using a cost-effective field programmable gate array (FPGA) and a micro control unit (MCU). As shown in the experimental results, the localization errors of the proposed system were less than 3 cm when an impulsive acoustic source was generated over 1 m away from the microphone array, which is comparable to a position-based system with reduced computational complexity. On the basis of the high accuracy and real-time performance of localizing an impulsive acoustic source, such as striking a ball, the proposed system can be applied to screen-based sports simulation.

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“…Moreover, FDAS with ridge detection (RD) and FDAS with RD and a deconvolution approach for the mapping of acoustic sources (DAMAS) [17] realized rapid acoustic-source localization as well as high resolution. Similarly, both generalized inverse beamforming (GIB) [18] and functional GIB (FGIB) [19] exhibited these characteristics using a double-layer microphone array.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional localization of point acoustic sources using a planar microphone array combined with beamforming

et al. 2018

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This paper presents a beamforming-based acoustic imaging (BBAI) method employing a two-dimensional (2D) microphone array that not only can locate an acoustic source in the XY plane parallel to the array, but can also identify the distance between the source and array in the Z direction, denoted as the source depth, and thus provides three-dimensional (3D) localization ability. In this method, the acoustic field is reconstructed on virtual XY planes at different distances along the Z direction. The source depth is then determined according to the virtual plane providing the maximum response of the acoustic field. The location of the source in the X and Y directions of the identified virtual plane can then be easily determined based on the standard beamforming principles of a planar array. The proposed BBAI method is evaluated based on simulations involving single- and multiple-point sources, and corresponding experimental evaluations are similarly conducted in an anechoic chamber. Both simulation and experimental results demonstrate that the proposed method is capable of locating acoustic sources in 3D space.

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Three-dimensional beamforming of dipolar aeroacoustic sources

Cited by 71 publications

References 25 publications

Improved algorithm of three-dimensional beamforming based on spatial cross-array

Improved algorithm of three-dimensional beamforming based on spatial cross-array

Screen-Based Sports Simulation Using Acoustic Source Localization

Three-dimensional localization of point acoustic sources using a planar microphone array combined with beamforming

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