315 research outputs found

    CABE : a cloud-based acoustic beamforming emulator for FPGA-based sound source localization

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    Microphone arrays are gaining in popularity thanks to the availability of low-cost microphones. Applications including sonar, binaural hearing aid devices, acoustic indoor localization techniques and speech recognition are proposed by several research groups and companies. In most of the available implementations, the microphones utilized are assumed to offer an ideal response in a given frequency domain. Several toolboxes and software can be used to obtain a theoretical response of a microphone array with a given beamforming algorithm. However, a tool facilitating the design of a microphone array taking into account the non-ideal characteristics could not be found. Moreover, generating packages facilitating the implementation on Field Programmable Gate Arrays has, to our knowledge, not been carried out yet. Visualizing the responses in 2D and 3D also poses an engineering challenge. To alleviate these shortcomings, a scalable Cloud-based Acoustic Beamforming Emulator (CABE) is proposed. The non-ideal characteristics of microphones are considered during the computations and results are validated with acoustic data captured from microphones. It is also possible to generate hardware description language packages containing delay tables facilitating the implementation of Delay-and-Sum beamformers in embedded hardware. Truncation error analysis can also be carried out for fixed-point signal processing. The effects of disabling a given group of microphones within the microphone array can also be calculated. Results and packages can be visualized with a dedicated client application. Users can create and configure several parameters of an emulation, including sound source placement, the shape of the microphone array and the required signal processing flow. Depending on the user configuration, 2D and 3D graphs showing the beamforming results, waterfall diagrams and performance metrics can be generated by the client application. The emulations are also validated with captured data from existing microphone arrays.</jats:p

    Optimal model-based beamforming and independent steering for spherical loudspeaker arrays

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    Spherical loudspeaker arrays have been recently studied for directional sound radiation, where the compact arrangement of the loudspeaker units around a sphere facilitated the control of sound radiation in three-dimensional space. Directivity of sound radiation, or beamforming, was achieved by driving each loudspeaker unit independently, where the design of beamforming weights was typically achieved by numerical optimization with reference to a given desired beam pattern. This is in contrast to the methods already developed for microphone arrays in general and spherical microphone arrays in particular, where beamformer weights are designed to satisfy a wider range of objectives, related to directivity, robustness, and side-lobe level, for example. This paper presents the development of a physical-model-based, optimal beamforming framework for spherical loudspeaker arrays, similar to the framework already developed for spherical microphone arrays, facilitating efficient beamforming in the spherical harmonics domain, with independent steering. In particular, it is shown that from a beamforming perspective, the spherical loudspeaker array is similar to the spherical microphone array with microphones arranged around a rigid sphere. Experimental investigation validates the theoretical framework of beamformer design

    Metrics for Evaluating the Spatial Accuracy of Microphone Arrays

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    The interest in 3D audio is constantly growing, thus leading to the appearance on the market of many microphone arrays for recording spatial audio, having a variety of sizes, number of channels and shapes, mostly spherical. Among the various characteristics that may have an influence on the quality of these systems, the presented work will deal with the spatial accuracy. The availability of robust methods for evaluating the spatial performance of the microphone arrays allows to compare the systems and to study the effect of different geometries, or beamforming algorithms. On one side, the design of new solutions can be optimized, on the other side a user can identify an optimal system depending on his needs. In this paper, two metrics for evaluating the spatial performance of microphone arrays are described, and two common formats for spatial audio are employed, Ambisonics and Spatial PCM Sampling (SPS). In the first part, the parameters Spatial Correlation and Level Difference are used for assessing the accuracy of the Ambisonics format, which is based on Spherical Harmonics functions. In the second part two classic metrics for loudspeakers, i.e., directivity factor and half power beam width, are employed for evaluating the accuracy of unidirectional virtual microphones, which constitute the base of the SPS format. In the last section, four well-known spherical microphone arrays are analyzed and compared through the described metrics and spatial audio formats

    Beamforming with double-sided, acoustically hard planar arrays

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    International audienceSeveral types of microphone arrays have been proposed for the purpose of capturing spatial audio signals. When the aim is to capture a full 3D sound field, the most obvious geometry is that of a sphere, and this is the array shape which has received the most attention from authors in this field. The wave equation and its solutions can be separated into the spherical coordinates, and for an internal problem like an open microphone array, the solutions are linear combinations of the well-known ambisonic basis functions. These lend themselves well to the analysis and optimization of spherical arrays. One important observation is that the radial part of these solutions is described by the spherical Bessel functions and that these oscillate around zero. This leads to the problem that a single-radius open array (i.e. one which does not perturb the sound field) will not be able to function over a wide frequency band.An open multi-radius array is able to overcome the problem by simultaneously sampling the Bessel functions at different points, chosen such that not all of them are zero at the same time. Another solution is to sample the sound field with a mixture of zeroth- and first-order microphones. Since the radial pressure gradient is maximal where the pressure crosses zero, these different microphone types can complement each other to produce a continuous coverage over a wide frequency range. However, the most popular solution to the problem is to mount zeroth-order microphones on a hard spherical shell. The scattering off the shell is maximal at those frequencies where the pressure of the incident field is zero at the radius of the shell. The resulting frequency response of the total sound field on the shell is a smooth function without zero crossings.Another geometry which has been studied for the same purpose is the planar array. This effectively samples the sound field in the x-y plane. The shape of the ambisonic basis functions is such that about half of them are zero in this plane. As with the spherical arrays, there are three possible solutions to this problem; the microphones can be replaced with a mixture of zeroth- and first-order microphones, the array can be comprised of several parallel layers of microphones, or a scattering surface can be introduced in the x-y plane, with zeroth-order microphones placed on both sides. A paper concerning this last solution has only recently been published. So far, these arrays have only been studied with regards to their suitability for capturing ambisonic signals.Among the studies that have been published concerning spherical arrays, several authors have proposed beamforming methods that perform better than methods that use ambisonic signals as an intermediate representation of the sound field. In particular, it has been shown that effective beamforming can be achieved beyond the frequencies where the ambisonic signals become unusable due to spatial aliasing.The current paper proposes beamforming methods for acoustically hard planar arrays and compares these with methods using intermediate ambisonic signals. The methods are tested numerically and experimentally on a 17 cm diameter disc-shaped array with 84 microphones in a 7-by-6-by-2 configuration (6 rings of 7 microphones on each side). The implications of these techniques on the optimal microphone layout of the array are addressed

    Design and Evaluation of a Scalable and Reconfigurable Multi-Platform System for Acoustic Imaging

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    This paper proposes a scalable and multi-platform framework for signal acquisition and processing, which allows for the generation of acoustic images using planar arrays of MEMS (Micro-Electro-Mechanical Systems) microphones with low development and deployment costs. Acoustic characterization of MEMS sensors was performed, and the beam pattern of a module, based on an 8 Ă— 8 planar array and of several clusters of modules, was obtained. A flexible framework, formed by an FPGA, an embedded processor, a computer desktop, and a graphic processing unit, was defined. The processing times of the algorithms used to obtain the acoustic images, including signal processing and wideband beamforming via FFT, were evaluated in each subsystem of the framework. Based on this analysis, three frameworks are proposed, defined by the specific subsystems used and the algorithms shared. Finally, a set of acoustic images obtained from sound reflected from a person are presented as a case study in the field of biometric identification. These results reveal the feasibility of the proposed systemSpanish research project SAM: TEC 2015-68170-R (MINECO/FEDER, UE

    Array signal processing for source localization and enhancement

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    “A common approach to the wide-band microphone array problem is to assume a certain array geometry and then design optimal weights (often in subbands) to meet a set of desired criteria. In addition to weights, we consider the geometry of the microphone arrangement to be part of the optimization problem. Our approach is to use particle swarm optimization (PSO) to search for the optimal geometry while using an optimal weight design to design the weights for each particle’s geometry. The resulting directivity indices (DI’s) and white noise SNR gains (WNG’s) form the basis of the PSO’s fitness function. Another important consideration in the optimal weight design are several regularization parameters. By including those parameters in the particles, we optimize their values as well in the operation of the PSO. The proposed method allows the user great flexibility in specifying desired DI’s and WNG’s over frequency by virtue of the PSO fitness function. Although the above method discusses beam and nulls steering for fixed locations, in real time scenarios, it requires us to estimate the source positions to steer the beam position adaptively. We also investigate source localization of sound and RF sources using machine learning techniques. As for the RF source localization, we consider radio frequency identification (RFID) antenna tags. Using a planar RFID antenna array with beam steering capability and using received signal strength indicator (RSSI) value captured for each beam position, the position of each RFID antenna tag is estimated. The proposed approach is also shown to perform well under various challenging scenarios”--Abstract, page iv

    Recording, Analysis and Playback of Spatial Sound Field using Novel Design Methods of Transducer Arrays

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    Nowadays, a growing interest in the recording and reproduction of spatial audio has been observed. With virtual and augmented reality technologies spreading fast thanks to entertainment and video game industries, also the professional opportunities in the field of engineering are evolving. However, despite many microphone arrays are reaching the market, most of them is not optimized for engineering or diagnostic use and remains mainly confined to voice and music recordings. In this thesis, the design of two new systems for recording and analysing the spatial distribution of sound energy, employing arrays of transducers and cameras, is discussed. Both acoustic and visual spatial information is recorded and combined together to produce static and dynamic colour maps, with a specially designed software and employing Ambisonics and Spatial PCM Sampling (SPS), two common spatial audio formats, for signals processing. The first solution consists in a microphone array made of 32 capsules and a circular array of eight cameras, optimized for low frequencies. The size of the array is designed accordingly to the frequency range of interest for automotive Noise, Vibration &amp; Harshness (NVH) applications. The second system is an underwater probe with four hydrophones and a panoramic camera, with which it is possible to monitor the effects of underwater noise produced by human activities on marine species. Finite Elements Method (FEM) simulations have been used to calculate the array response, thus deriving the filtering matrix and performing theoretical evaluation of the spatial performance. Field tests of the proposed solutions are presented in comparison with the current state-of-the-art equipment. The faithful reproduction of the spatial sound field arouses equally interest. Hence, a method to playback panoramic video with spatial audio is presented, making use of Virtual Reality (VR) technology, spatial audio, individualized Head Related Transfer Functions (HRTFs) and personalized headphones equalization. The work in its entirety presents a complete methodology for recording, analysing and reproducing the spatial information of soundscapes

    Eigenbeamforming array systems for sound source localization

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