球谐域自适应混响抵消与声源定位算法

提出了一种基于球谐域的自适应混响抵消与声源定位算法,该方法通过去混响处理改善语音质量,并提高球谐域定位算法在混响环境下的定位性能。推导了基于多通道线性预测的自适应混响抵消算法在球谐域的表达式,针对刚球模型提出分阶处理的去混响方法,并对去混响后的信号进行波达方向估计。采用32元球阵的仿真结果表明,相比于球谐域不分阶去混响方法,该方法最大可减少约2/3的运算量,同时语音PESQ得分及SRMR均显著提高。利用实验数据对算法性能进行测试,实验结果验证了该方法在实际声学环境中去混响和声源定位的有效性。      

Acoustic analysis by spherical microphone array processing of room impulse responses

Spherical microphone arrays have been recently used for room acoustics analysis, to detect the direction-of-arrival of early room reflections, and compute directional room impulse responses and other spatial room acoustics parameters. Previous works presented methods for room acoustics analysis using spherical arrays that are based on beamforming, e.g., delay-and-sum, regular beamforming, and Dolph-Chebyshev beamforming. Although beamforming methods provide useful directional selectivity, optimal array processing methods can provide enhanced performance. However, these algorithms require an array cross-spectrum matrix with a full rank, while array data based on room impulse responses may not satisfy this condition due to the single frame data. This paper presents a smoothing technique for the cross-spectrum matrix in the frequency domain, designed for spherical microphone arrays, that can solve the problem of low rank when using room impulse response data, therefore facilitating the use of optimal array processing methods. Frequency smoothing is shown to be performed effectively using spherical arrays, due to the decoupling of frequency and angular components in the spherical harmonics domain. Experimental study with data measured in a real auditorium illustrates the performance of optimal array processing methods such as MUSIC and MVDR compared to beamforming.     

基于压缩感知的矢量阵聚焦定位方法

本文针对噪声源近场定位识别问题,利用声源分布在空间域具有稀疏性,在压缩感知理论框架下建立了新体系下的矢量阵聚焦波束形成方法,用于解决同频相干声源的定位识别问题.新方法可在小快拍下准确获得噪声源的空间位置,且不损失对噪声源贡献相对大小的评价能力.通过详细的理论推导、仿真分析和试验验证,证明了基于压缩感知的矢量阵聚焦定位新方法本质上实现了l1范数正则化求解下的波形恢复和空间谱估计,因此具有较高的定位精度,较强的相干声源分辨能力、准确的声源贡献相对大小评价能力以及较高的背景压制能力,可应用于水下复杂噪声源的定位识别.     

A directional acoustic array using silicon micromachined piezoresistive microphones

The need for noise source localization and characterization has driven the development of advanced sound field measurement techniques using microphone arrays. Unfortunately, the cost and complexity of these systems currently limit their widespread use. Directional acoustic arrays are commonly used in wind tunnel studies of aeroacoustic sources and may consist of hundreds of condenser microphones. A microelectromechanical system (MEMS)-based directional acoustic array system is presented to demonstrate key technologies to reduce the cost, increase the mobility, and improve the data processing efficiency versus conventional systems. The system uses 16 hybrid-packaged MEMS silicon piezoresistive microphones that are mounted to a printed circuit board. In addition, a high-speed signal processing system was employed to generate the array response in near real time. Dynamic calibrations of the microphone sensor modules indicate an average sensitivity of 831 microV/Pa with matched magnitude (+/-0.6 dB) and phase (+/-1 degree) responses between devices. The array system was characterized in an anechoic chamber using a monopole source as a function of frequency, sound pressure level, and source location. The performance of the MEMS-based array is comparable to conventional array systems and also benefits from significant cost savings.     

基于声传播算子的声源定位实验模拟方法研究

声传播算子是一种高效的时域声场计算方法,它能够很方便地计算出给定系统参数下任意时刻任意位置的声场变化情况,本文采用这种方法计算所得的二维房间声场信息进行传声器阵列的声源定位仿真实验。计算结果表明,用该方法获取的阵列数据能有效地应用于阵列信号处理算法中,准确地估计出初始高斯脉冲声源的方向。声传播算子声场计算方法能为传声器阵列声源定位的实验提供方便,使得传声器阵列声源定位算法在不同混响时间的鲁棒性实验研究变得更加简捷。     

单层传声器阵列信号空间重采样的声波分离方法

为了重构非自由声场中目标声源的声场响应,提出单层传声器阵列信号空间重采样的声波分离方法.以球面波函数为基函数,建立由系列球面波函数叠加表达的声场数学模型.基于近场声全息原理,利用单层传声器阵列面上空间重采样形成的两组声压测量信号,求解基函数系数,并重构出传声器阵列两侧声源各自的声场响应,实现声波分离.使用脉动球和振动球共同作用的非自由声场,检验了数学模型以及传声器信号信噪比、传声器阵列形状和面积、声源中心位置、频率等关键参数对声波分离精度的影响,并在全消声室内进行了实验验证.最后,对单层传声器阵列重采样的声波分离方法的实施给出了建议.     

High-resolution plane-wave decomposition in an auditorium using a dual-radius scanning spherical microphone array

The spatial and temporal distribution of early reflections in an auditorium is considered important for sound perception. Previous studies presented measurement and analysis methods based on spherical microphone arrays and plane-wave decomposition that could provide information on the direction and time of arrival of early reflections. This paper presents recent results of room acoustics analysis based on a spherical microphone array, which employs high spherical harmonics order for improved spatial resolution, and a dual-radius spherical measurement array to avoid ill-conditioning at the null frequencies of the spherical Bessel function. Spatial-temporal analysis is performed to produce directional impulse responses, while analysis based on the windowed Fourier transform is employed to detect direction of arrival of individual reflections at selected frequencies. Experimental results of sound-field analysis in a real auditorium are also presented.     

Blind extraction and localization of sound sources using point sources based approaches

This paper presents theoretical models for blind sound source localization and separation of the signals emitted by arbitrary point sources in free space. Source localizations are achieved by a model based approach that accounts for the spherical spreading of an acoustic wave and utilizes an iterative triangulation, based on the signals measured by a three-dimensional microphone array. Once source locations are determined, the source signals are separated by using the point source separation (PSS) method, which is valid for all types of signals, including harmonic, continuous, transient, random, narrowband and broadband. General solutions for signals separation are presented. Theoretically, PSS can reconstruct the individual source signals exactly. This is because it employs the free-space Green's function, which defines the exact correlation among individual sources and measurement microphones. To validate PSS, numerical simulations are carried out and results are compared with those obtained by FastICA (Independent Component Analysis) code. The impacts of various parameters such as the microphone configuration, type of source signals, signal to noise ratio, number of microphones and source localization errors on the quality of signals separation by using PSS and FastICA are examined. The advantages and disadvantages of PSS and FastICA are compared and discussed.     

Multichannel time-reversal processing for acoustic communications in a highly reverberant environment

The development of time-reversal (T/R) communication systems is a recent signal processing research area dominated by applying T/R techniques to communicate in hostile environments. The fundamental concept is based on time-reversing the impulse response or Green's function characterizing the uncertain communications channel to mitigate deleterious dispersion and multipath effects. In this paper, we extend point-to-point to array-to-point communications by first establishing the basic theory to define and solve the underlying multichannel communications problem and then developing various realizations of the resulting T/R receivers. We show that not only do these receivers perform well in a hostile environment, but they also can be implemented with a "1 bit" analog-to-digital converter design structure. We validate these results by performing proof-of-principle acoustic communications experiments in air. It is shown that the resulting T/R receivers are capable of extracting the transmitted coded sequence from noisy microphone array measurements with zero-bit error.     

Spatial structure of low-frequency wind noise

The distinguishing spatial properties of low-frequency microphone wind noise (turbulent pressure disturbances) are examined with a planar, 49-element array. Individual, propagating transient pressure disturbances are imaged by wavelet processing to the array data. Within a given frequency range, the wind disturbances are much smaller and less spatially coherent than sound waves. Conventional array processing techniques are particularly sensitive to wind noise when sensor separations are small compared to the acoustic wavelengths of interest.     

传声器阵列对高频弱声源的声成像识别方法

研究了传声器阵列对高频弱声源的识别定位方法。该方法根据高频声源的指向性和阵列探测特性等特点,提出了利用信噪比加权方法提高有效阵元对声成像的贡献,根据信噪比的大小对每个阵元添加不同的权值,可以显著提高传声器阵列对高频弱声源的声像清晰度。仿真分析了阵元加权和不加权两种方法对阵列声成像结果的影响,以某型号笔记本电脑电路板噪声为对象进行的实验表明,在阵列测量中充分利用有效阵元信号可以实现对声压级低达10~20dB的微弱噪声源的精确测量。      

Kalman filter-based microphone array signal processing using the equivalent source model

This paper demonstrates that microphone array signal processing can be implemented by using adaptive model-based filtering approaches. Nearfield and farfield sound propagation models are formulated into state-space forms in light of the Equivalent Source Method (ESM). In the model, the unknown source amplitudes of the virtual sources are adaptively estimated by using Kalman filters (KFs). The nearfield array aimed at noise source identification is based on a Multiple-Input–Multiple-Output (MIMO) state-space model with minimal realization, whereas the farfield array technique aimed at speech quality enhancement is based on a Single-Input–Multiple-Output (SIMO) state-space model. Performance of the nearfield array is evaluated in terms of relative error of the velocity reconstructed on the actual source surface. Numerical simulations for the nearfield array were conducted with a baffled planar piston source. From the error metric, the proposed KF algorithm proved effective in identifying noise sources. Objective simulations and subjective experiments are undertaken to validate the proposed farfield arrays in comparison with two conventional methods. The results of objective tests indicated that the farfield arrays significantly enhanced the speech quality and word recognition rate. The results of subjective tests post-processed with the analysis of variance (ANOVA) and a post-hoc Fisher's least significant difference (LSD) test have shown great promise in the KF-based microphone array signal processing techniques.     

基于双传声器对的多声源二维定位跟踪算法

提出一种房间混响声场环境下的多声源二维定位跟踪算法。研究了基于盲源分离的时延估计,以及联合空间分布的多个传声器对的定位算法。用高斯似然函数解决在多源、多维情况下声源定位的时延匹对模糊问题,使之能够用双传声器对实现对多个声源的二维定位,结合粒子滤波算法实现对多个运动声源的跟踪。仿真实验验证了提出算法的有效性。      

Acoustic centering of sources measured by surrounding spherical microphone arrays

The radiation patterns of acoustic sources have great significance in a wide range of applications, such as measuring the directivity of loudspeakers and investigating the radiation of musical instruments for auralization. Recently, surrounding spherical microphone arrays have been studied for sound field analysis, facilitating measurement of the pressure around a sphere and the computation of the spherical harmonics spectrum of the sound source. However, the sound radiation pattern may be affected by the location of the source inside the microphone array, which is an undesirable property when aiming to characterize source radiation in a unique manner. This paper presents a theoretical analysis of the spherical harmonics spectrum of spatially translated sources and defines four measures for the misalignment of the acoustic center of a radiating source. Optimization is used to promote optimal alignment based on the proposed measures and the errors caused by numerical and array-order limitations are investigated. This methodology is examined using both simulated and experimental data in order to investigate the performance and limitations of the different alignment methods.     

基于蒙特卡罗法的实时空间三维声源定位

构建了一个基于四个声音传感器的信号时延采集系统,根据采集系统得到的三个时间差和传感器的响应顺序,提出了一种基于蒙特卡罗法实时空间的三维声源定位算法.该算法通过三维声音定位的非线性方程,构建一个三维模函数,通过寻找空间全局收敛点,并根据公差容限进行变步长搜索,准确快速地计算出声源的位置.     

Multiple-array passive acoustic source localization in urban environments

In many situations of interest, obstacles to acoustic wave propagation such as terrain or buildings exist that provide unique challenges to localization. These obstacles introduce multiple propagation paths, reflections, and diffraction into the propagation. In this paper, matched field processing is proposed as an effective method of acoustic localization in a two dimensional scattering environment. Numerical techniques can be used to model complex propagation in a space where analytical solutions are not feasible. Realistically, there is always some uncertainty in model parameters that in turn can adversely affect localization ability. In particular, uncertainty in array location, sound speed, and various parameters affecting inter-array coherence only are investigated. A spatially distributed, multiarray network is shown to mitigate the effects of uncertainty. Multiarray inverse filter processing techniques are evaluated through perturbation of uncertain model parameters. These techniques are more accurate and flexible to implement than other matched field processing methods such as time reversal.     

Spherical harmonics MUSIC versus conventional MUSIC

With the three-dimensional symmetry and wide potential application, spherical array signal processing has been a hot research area for years. This paper devotes to the direction-of-arrival (DOA) estimation of the spherical arrays. Based on the orthogonality of the sensors’ location, MUSIC algorithm in spherical space is proposed, named as SH-MUSIC. Similar to beamspace MUSIC, spherical harmonics transformation is operated before MUSIC algorithm and a better performance is gotten because SH-MUSIC utilizes the array configuration’s orthogonality. On account of the transformation matrix’s orthogonality, spherical harmonics transformation is suggested to be operated firstly in other improved MUSIC algorithms without rejection, and it is demonstrated in beamspace MUSIC. In addition, owing to the tiny error between the steering vectors and the spherical harmonics with high order, sphere array data models including open sphere and rigid sphere are constructed. Simulation proves SH-MUSIC to be effective. Moreover, experimental data from a rigid sphere microphone array is dealt with by SH-MUSIC and the DOAs are estimated accurately.     

A system for simulating room acoustical environments for one’s own voice

The real-time simulation of room acoustical environments for one’s own voice using generic software has been difficult until very recently due to the computational load involved: requiring real-time convolution of a person’s voice with a potentially large number of long room impulse responses. This paper describes a software-based solution that accomplishes real-time convolution with head-tracking to simulate the effect of room acoustical environments on the sound of one’s own voice, using binaural technology. Actual rooms are characterized by measuring the room impulse response from the mouth to ears of the same head (oral binaural room impulse response, OBRIR). By repeating this process at 2° yaw increments for a given head position, the rooms are binaurally scanned around a given position to obtain a collection of OBRIRs, which is then used by the software-based simulation system. In the simulated rooms, a person equipped with a near-mouth microphone and near-ear loudspeakers can speak or sing and hear their voice, as it would sound in the recorded rooms, while physically being in an anechoic room. By continually updating the person’s head orientation using head-tracking, the corresponding OBRIR is chosen for convolution with their voice. The system described in this paper achieves the low latency that is required to simulate nearby reflections, and it can perform convolution with long room impulse responses.     

Beamforming array techniques for acoustic emission monitoring of large concrete structures

This paper introduces a novel method of acoustic emission (AE) analysis which is particularly suited for field applications on large plate-like reinforced concrete structures, such as walls and bridge decks. Similar to phased-array signal processing techniques developed for other non-destructive evaluation methods, this technique adapts beamforming tools developed for passive sonar and seismological applications for use in AE source localization and signal discrimination analyses. Instead of relying on the relatively weak P-wave, this method uses the energy-rich Rayleigh wave and requires only a small array of 4–8 sensors. Tests on an in-service reinforced concrete structure demonstrate that the azimuth of an artificial AE source can be determined via this method for sources located up to 3.8 m from the sensor array, even when the P-wave is undetectable. The beamforming array geometry also allows additional signal processing tools to be implemented, such as the VESPA process (VElocity SPectral Analysis), whereby the arrivals of different wave phases are identified by their apparent velocity of propagation. Beamforming AE can reduce sampling rate and time synchronization requirements between spatially distant sensors which in turn facilitates the use of wireless sensor networks for this application.     

Evaluation of generalized cross-correlation methods for direction of arrival estimation using two microphones in real environments

The localization of sound sources, and particularly speech, has a numerous number of applications to the industry. This has motivated a continuous effort in developing robust direction-of-arrival detection algorithms, in order to overcome the limitations imposed by real scenarios, such as multiple reflections and undesirable noise sources. Time difference of arrival-based methods, and particularly, generalized cross-correlation approaches have been widely investigated in acoustic signal processing, but there is considerable lack in the technical literature about their evaluation in real environments when only two microphones are used. In this work, four generalized cross-correlation methods for localization of speech sources with two microphones have been analyzed in different real scenarios with a stationary noise source. Furthermore, these scenarios have been acoustically characterized, in order to relate the behavior of these cross-correlation methods with the acoustic properties of noisy scenarios. The scope of this study is not only to assess the accuracy and reliability of a set of well-known localization algorithms, but also to determine how the different acoustic properties of the room under analysis have a determinant influence in the final results, by incorporating in the analysis additional factors to the reverberation time and signal-to-noise ratio. Results of this study have outlined the influence of the acoustic properties analysed in the performance of these methods.