运动声源快速定位的声达时差法

针对声达时差法只能用于非运动声源定位的问题,本文提出一种运动声源快速定位方法。该方法以声达时差为基本定位原理,基于声源计算位置对多普勒效应进行解耦并进行声信号多普勒效应修正,根据三角定位方法构建声传播空间矩阵,以声源位置偏差度为目标基于单纯形优化搜索算法进行声源位置快速逼近,实现了对匀速直线运动的单声源的定位追踪,提高定位实时性。该方法将声达时差法拓展到运动声源的定位,同时解决了消除多普勒效应带来的计算过程复杂、运算量大的问题,仅用4个传声器就可实现运动声源的快速定位,突破了传统运动声源识别中对大传声器阵列的依赖。仿真实验和实车运动声源识别实验结果证明了该方法的有效性,本研究为短时发声运动声源的识别提供了一种简便、高效的方法。     

The influence of pinnae-based spectral cues on sound localization

The role of pinnae-based spectral cues was investigated by requiring listeners to locate sound, binaurally, in the horizontal plane with and without partial occlusion of their external ears. The main finding was that the high frequencies were necessary for optimal performance. When the stimulus contained the higher audio frequencies, e.g., broadband and 4.0-kHz high-pass noise, localization accuracy was significantly superior to that recorded for stimuli consisting only of the lower frequencies (4.0- and 1.0-kHz low-pass noise). This finding was attributed to the influence of the spectral cues furnished by the pinnae, for when the stimulus composition included high frequencies, pinnae occlusion resulted in a marked decline in localization accuracy. Numerous front-rear reversals occurred. Moreover, the ability to distinguish among sounds originating within the same quadrant also suffered. Performance proficiency for the low-pass stimuli was not further degraded under conditions of pinnae occlusion. In locating the 4.0-kHz high-pass noise when both, neither, or only one ear was occluded, the data demonstrated unequivocally that the pinna-based cues of the "near" ear contributed powerfully toward localization accuracy.     

The effect of multimicrophone noise reduction systems on sound source localization by users of binaural hearing aids

This paper evaluates the influence of three multimicrophone noise reduction algorithms on the ability to localize sound sources. Two recently developed noise reduction techniques for binaural hearing aids were evaluated, namely, the binaural multichannel Wiener filter (MWF) and the binaural multichannel Wiener filter with partial noise estimate (MWF-N), together with a dual-monaural adaptive directional microphone (ADM), which is a widely used noise reduction approach in commercial hearing aids. The influence of the different algorithms on perceived sound source localization and their noise reduction performance was evaluated. It is shown that noise reduction algorithms can have a large influence on localization and that (a) the ADM only preserves localization in the forward direction over azimuths where limited or no noise reduction is obtained; (b) the MWF preserves localization of the target speech component but may distort localization of the noise component. The latter is dependent on signal-to-noise ratio and masking effects; (c) the MWF-N enables correct localization of both the speech and the noise components; (d) the statistical Wiener filter approach introduces a better combination of sound source localization and noise reduction performance than the ADM approach.     

A study on the random array generation method for moving sound source identification

Based on the problem that the generating method of random array structure is inefficient,a method is proposed to generate the random target arrays by using coaxial circular array in the polar coordinates in the premise that the array angular resolution of source identification is guaranteed.According to the principle of moving sound source identification,this work deduces the basic non-equidistance coaxial circular rings'radius,and generates target random arrays which were suitable for moving sound source identification through array partitioning,condition filtering in the polar coordinates and simulation evaluation.Finally,numerical simulation and moving car sound source identification test have been done.The analytical results show that using this method to generate random array is effective.Compared with the traditional regular arrays,the target random array has more accurate moving sound source identification performance.     

The influence of signal parameters on the sound source localization ability of a harbor porpoise (Phocoena phocoena)

It is unclear how well harbor porpoises can locate sound sources, and thus can locate acoustic alarms on gillnets. Therefore the ability of a porpoise to determine the location of a sound source was determined. The animal was trained to indicate the active one of 16 transducers in a 16-m-diam circle around a central listening station. The duration and received level of the narrowband frequency-modulated signals (center frequencies 16, 64 and 100 kHz) were varied. The animal's localization performance increased when the signal duration increased from 600 to 1000 ms. The lower the received sound pressure level (SPL) of the signal, the harder the animal found it to localize the sound source. When pulse duration was long enough (approximately 1 s) and the received SPLs of the sounds were high (34-50 dB above basic hearing thresholds or 3-15 dB above the theoretical masked detection threshold in the ambient noise condition of the present study), the animal could locate sounds of the three frequencies almost equally well. The porpoise was able to locate sound sources up to 124 degrees to its left or right more easily than sounds from behind it.     

Material sound source localization through headphones

In the present paper a study of sound localization is carried out, considering two different sounds emitted from different hit materials (wood and bongo) as well as a Delta sound. The motivation of this research is to study how humans localize sounds coming from different materials, with the purpose of a future implementation of the acoustic sounds with better localization features in navigation aid systems or training audio-games suited for blind people. Wood and bongo sounds are recorded after hitting two objects made of these materials. Afterwards, they are analysed and processed. On the other hand, the Delta sound (click) is generated by using the Adobe Audition software, considering a frequency of 44.1 kHz. All sounds are analysed and convolved with previously measured non-individual Head-Related Transfer Functions both for an anechoic environment and for an environment with reverberation. The First Choice method is used in this experiment. Subjects are asked to localize the source position of the sound listened through the headphones, by using a graphic user interface. The analyses of the recorded data reveal that no significant differences are obtained either when considering the nature of the sounds (wood, bongo, Delta) or their environmental context (with or without reverberation). The localization accuracies for the anechoic sounds are: wood 90.19%, bongo 92.96% and Delta sound 89.59%, whereas for the sounds with reverberation the results are: wood 90.59%, bongo 92.63% and Delta sound 90.91%. According to these data, we can conclude that even when considering the reverberation effect, the localization accuracy does not significantly increase.     

The influence of duration and level on human sound localization

The localization of sounds in the vertical plane (elevation) deteriorates for short-duration wideband sounds at moderate to high intensities. The effect is described by a systematic decrease of the elevation gain (slope of stimulus-response relation) at short sound durations. Two hypotheses have been proposed to explain this finding. Either the sound localization system integrates over a time window that is too short to accurately extract the spectral localization cues (neural integration hypothesis), or the effect results from cochlear saturation at high intensities (adaptation hypothesis). While the neural integration model predicts that elevation gain is independent of sound level, the adaptation hypothesis holds that low elevation gains for short-duration sounds are only obtained at high intensities. Here, these predictions are tested over a larger range of stimulus parameters than has been done so far. Subjects responded with rapid head movements to noise bursts in the two-dimensional frontal space. Stimulus durations ranged from 3 to 100 ms; sound levels from 26 to 73 dB SPL. Results show that the elevation gain decreases for short noise bursts at all sound levels, a finding that supports the integration model. On the other hand, the short-duration gain also decreases at high sound levels, which is in line with the adaptation hypothesis. The finding that elevation gain was a nonmonotonic function of sound level for all sound durations, however, is predicted by neither model. It is concluded that both mechanisms underlie the elevation gain effect and a conceptual model is proposed to reconcile these findings.     

风场环境中声速修正的分布式声源定位算法

为减小声速误差对定位精度的影响,提出了一种基于声速修正的分布式声源定位方法。首先,将声速表示为未知声源位置的函数,逼近风场中的声速场分布,然后将其代入TDOA (Time Differences of Arrival)算法中,构建非线性超定方程组,最后采用粒子群优化算法求解声源位置。对不同风速、不同声源位置及不同测试区域进行仿真,结果表明:修正后的定位精度比修正前有明显提高,尤其对于大范围并且声源靠近测试区域边缘位置的定位系统,改善更加明显;4个节点的定位系统实验结果表明,修正后的定位误差可降至修正前的4l%,该方法能更好的应用于风场中的定位系统。     

识别运动声源随机阵列生成法研究

针对随机阵列结构设计方面欠缺高效的生成方法这一问题,在保证阵列对声源识别精度的前提下,提出一种在极坐标下用于识别运动声源的随机阵列生成方法。根据声阵列识别运动声源的原理,推导了非等间距基本同轴圆环的半径,再通过降列分区、极坐标下条件筛选和模拟评价三个步骤,生成适用于识别运动声源的目标随机阵列,最后进行数值模拟和运动汽车噪声源识别实验进行验证。研究结果表明,用该方法能够高效地生成目标随机阵列,与常用规则阵列相比具有更良好的声源识别特性,并且具有准确的运动声源识别性能。     

识别运动声源随机阵列生成法研究

针对随机阵列结构设计方面欠缺高效的生成方法这一问题,在保证阵列对声源识别精度的前提下,提出一种在极坐标下用于识别运动声源的随机阵列生成方法。根据声阵列识别运动声源的原理,推导了非等间距基本同轴圆环的半径,再通过降列分区、极坐标下条件筛选和模拟评价三个步骤,生成适用于识别运动声源的目标随机阵列,最后进行数值模拟和运动汽车噪声源识别实验进行验证。研究结果表明,用该方法能够高效地生成目标随机阵列,与常用规则阵列相比具有更良好的声源识别特性,并且具有准确的运动声源识别性能。     

频率对环绕声声像定位的影响

本文考虑双耳相位差的高级近似，导出了中频情况下适用的具有更普遍意义的平面环绕声声像定位公式。在低频时该式将化为通常的环绕声声像定位公式，而随着声音频率的增加，声像位置将与频率有关。将新的公式用到方型排列和棱型排列的４－４－４环绕声系统，得到了同实验相一致的结果。文中着重指出，声像随频率而变化是导致环绕声重发中侧向声像不稳定的重要在而为今后改进环绕声系统提供了理论基础。     

Non-line-of-sight sound source localization using matched-field processing

Acoustic diffraction allows sound to travel around opaque objects and therefore may allow beyond-line-of-sight sensing of remote sound sources. This paper reports simulated and experimental results for localizing sound sources based on fully shadowed microphone array measurements. The generic geometry includes a point source, a solid 90° wedge, and a receiving array that lies entirely in the shadow defined by the source location and the wedge. Source localization performance is assessed via matched-field (MF) ambiguity surfaces as a function of receiving array configuration, and received signal-to-noise ratio for the Bartlett and minimum variance distortionless (MVD) MF processors. Here, the sound propagation model is developed from a Green's function integral treatment. A simple 16 element line array of microphones is tested in three mutually orthogonal orientations. The experiments were conducted using an approximate 50-to-1-scaled tabletop model of a blind city-street intersection and produced ambiguity surfaces from source frequencies between 17.5 and 19 kHz that were incoherently summed. The experimental results suggest that a sound source may be localized by the MVD processor when using fully shadowed arrays that have significant aperture parallel to the edge of the wedge. However, this performance is reduced significantly for signal-to-noise ratios below 40 dB.     

Auditory filter based broadband MUSIC algorithm for sound source localization

Based on the analysis of the shortcomings of broadband MUSIC algorithm with short-time Fourier transform （SF-MUSIC） for sound source localization, a broadband MUSIC algorithm with auditory filter （AF-MUSIC） was proposed. The proposed algorithm first em- ploys auditory filter bank to decompose the signals received on the microphone array, and then locates the sound source with MUSIC algorithm over every frequency channel. At last, by combining with the subinterval frequency estimation, the final localization result is gained. Evaluations on the proposed algorithm prove that comparing with the SF-MUSIC algorithm, the AF-MUSIC algorithm decreases the average error of the estimation results with 2.5479 de- gree in different source conditions. The accuracy of sound source DOA estimation is enhanced effectively.     

Fly-ear inspired micro-sensor for sound source localization in two dimensions

Inspired by the hearing organ of the fly Ormia ochracea, a miniature sound localization sensor is developed, which can be used to pinpoint a sound source in two dimensions described by the azimuth and elevation angles. The sensor device employs an equilateral triangle configuration consisting of three mechanically coupled circular membranes whose oscillations are detected by a fiber-optic system. The experimental results indicate that significant amplification of the directional cues and directional sensitivity can be achieved with the fly-ear inspired sensor design. This work can provide a basis for the development of miniature sound localization sensors in two dimensions.     

空气中声源的水下匹配场定位

通过水下布放的垂直线列阵采集空中声源在水下激发的测量声场,采用声场波数积分模型(OASES模型)对空中声源激发的水下声场建模,计算出拷贝声场,将二者进行匹配处理从而对空中声源目标定位。首先通过数值仿真验证了匹配场处理技术对空中声源的测距能力,并通过引入宽带匹配场处理器平滑掉距离上的周期性旁瓣。最后分析南海某海域的空气声试验数据,采用常规匹配场方法对700 m以内的32组空中声源目标进行定位,测距结果与GPS计算的收发间实际距离相比,大多数情况下是一致的,在较远距离由于信噪比降低,测量结果容易出现偏差。     

Distributed sound source localization algorithm with sound velocity calibration in windy environments

A new sound source localization method with sound speed compensation is proposed to reduce the wind influence on the performance of conventional TDOA(Time Difference of Arrival) algorithms. First, the sound speed is described as a set of functions of the unknown source location, to approximate the acoustic velocity field distribution in the wind field. Then,they are introduced into the TDOA algorithm, to construct nonlinear equations. Finally, the particle swarm optimization algorithm is used to estimate the source location. The simulation results show that the proposed algorithm can significantly improve the localization accuracy for different wind velocities, source locations and test area sizes. The experimental results show that the proposed method can reduce localization errors to about 40% of the original error in a four nodes localization system.     

Improved steered response power method for sound source localization based on principal eigenvector

Sound source localization is essential in many microphone arrays application, ranging from teleconferencing systems to artificial perception in a reverberant noisy environment. The steered response power (SRP) using the phase transform (SRP-PHAT) source localization algorithm has been proved robust, however, the performance of the SRP-PHAT algorithm degrades in highly reverberant noisy environment. Though the SRP-based maximum likelihood localizers are more robust than SRP-PHAT, they have the drawback of requiring noise variance to be estimated in a silent room. This paper presents an improved SRP-PHAT algorithm based on principal eigenvector. Sound source location is estimated from the principal eigenvector computed from the frequency-domain correlation matrix. Using both simulated and real data, we show that the proposed algorithm achieves higher source localization accuracy compared to the SRP-PHAT algorithm.     

声源定位实验——一个具有明确应用背景和前沿技术特点的综合性实验

研制开发了一种进行声源定位的实验装置.利用波的传播特性,可以推知物体的空间位置.文章介绍了声发射平面定位的原理,自制的实验装置和实验结果.     

Boundary element model for simulating sound propagation and source localization within the lungs

An acoustic boundary element (BE) model is used to simulate sound propagation in the lung parenchyma. It is computationally validated and then compared with experimental studies on lung phantom models. Parametric studies quantify the effect of different model parameters on the resulting acoustic field within the lung phantoms. The BE model is then coupled with a source localization algorithm to predict the position of an acoustic source within the phantom. Experimental studies validate the BE-based source localization algorithm and show that the same algorithm does not perform as well if the BE simulation is replaced with a free field assumption that neglects reflections and standing wave patterns created within the finite-size lung phantom. The BE model and source localization procedure are then applied to actual lung geometry taken from the National Library of Medicine's Visible Human Project. These numerical studies are in agreement with the studies on simpler geometry in that use of a BE model in place of the free field assumption alters the predicted acoustic field and source localization results. This work is relevant to the development of advanced auscultatory techniques that utilize multiple noninvasive sensors to construct acoustic images of sound generation and transmission to identify pathologies.