Efficient Continuous Beam Steering for Planar Arrays of Differential Microphones

Performing continuous beam steering, from planar arrays of high-order differential microphones, is not trivial. The main problem is that shape-preserving beams can be steered only in a finite set of privileged directions, which depend on the position and the number of physical microphones. In this letter, we propose a simple and computationally inexpensive method for alleviating this problem using planar microphone arrays. Given two identical reference beams pointing in two different directions, we show how to build a beam of nearly constant shape, which can be continuously steered between such two directions. The proposed method, unlike the diffused steering approaches based on linear combinations of eigenbeams (spherical harmonics), is applicable to planar arrays also if we deal with beams characterized by high-order polar patterns. Using the coefficients of the Fourier series of the polar patterns, we also show how to find a tradeoff between shape invariance of the steered beam, and maximum angular displacement between the two reference beams. We show the effectiveness of the proposed method through the analysis of models based on first-, second-, and third-order differential microphones

Design exploration and performance strategies towards power-efficient FPGA-based achitectures for sound source localization

Many applications rely on MEMS microphone arrays for locating sound sources prior to their execution. Those applications not only are executed under real-time constraints but also are often embedded on low-power devices. These environments become challenging when increasing the number of microphones or requiring dynamic responses. Field-Programmable Gate Arrays (FPGAs) are usually chosen due to their flexibility and computational power. This work intends to guide the design of reconfigurable acoustic beamforming architectures, which are not only able to accurately determine the sound Direction-Of-Arrival (DoA) but also capable to satisfy the most demanding applications in terms of power efficiency. Design considerations of the required operations performing the sound location are discussed and analysed in order to facilitate the elaboration of reconfigurable acoustic beamforming architectures. Performance strategies are proposed and evaluated based on the characteristics of the presented architecture. This power-efficient architecture is compared to a different architecture prioritizing performance in order to reveal the unavoidable design trade-offs

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

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

MICROPHONE ARRAY OPTIMIZATION IN IMMERSIVE ENVIRONMENTS

The complex relationship between array gain patterns and microphone distributions limits the application of traditional optimization algorithms on irregular arrays, which show enhanced beamforming performance for human speech capture in immersive environments. This work analyzes the relationship between irregular microphone geometries and spatial filtering performance with statistical methods. Novel geometry descriptors are developed to capture the properties of irregular microphone distributions showing their impact on array performance. General guidelines and optimization methods for regular and irregular array design are proposed in immersive (near-field) environments to obtain superior beamforming ability for speech applications. Optimization times are greatly reduced through the objective function rules using performance-based geometric descriptions of microphone distributions that circumvent direct array gain computations over the space of interest. In addition, probabilistic descriptions of acoustic scenes are introduced to incorporate various levels of prior knowledge for the source distribution. To verify the effectiveness of the proposed optimization methods, simulated gain patterns and real SNR results of the optimized arrays are compared to corresponding traditional regular arrays and arrays obtained from direct exhaustive searching methods. Results show large SNR enhancements for the optimized arrays over arbitrary randomly generated arrays and regular arrays, especially at low microphone densities. The rapid convergence and acceptable processing times observed during the experiments establish the feasibility of proposed optimization methods for array geometry design in immersive environments where rapid deployment is required with limited knowledge of the acoustic scene, such as in mobile platforms and audio surveillance applications

Measurement-Based Modal Beamforming Using Planar Circular Microphone Arrays

This paper describes how to use a planar circular pressure-zone table-top microphone array for modal beamforming. Its goals are similar as for spherical arrays: higher-order resolution and a more-or-less steering-invariant beampattern design in the three-dimensional half space. As conventional circular arrays lack control of the beampattern in the vertical array plane, the proposed arrangement tries to fix this shortcoming to allow both horizontal and vertical control of beamforming. To provide a fully calibrated decomposition into the directional modes, the proposed beamforming approach is based on measurement data. From a MIMO (multiple-input-multiple-output) system description of the measurement data in the spherical harmonics domain, an inverse MIMO system of filters is designed for decomposing the microphone array signals into those spherical components eligible for modal beamforming. For an efficient measurement and robust set of decomposition filters, a reduced set of measurement positions and a regularisation strategy is suggested

Implementation and evaluation of a low complexity microphone array for speaker recognition

Includes bibliographical references (leaves 83-86).This thesis discusses the application of a microphone array employing a noise canceling beamforming technique for improving the robustness of speaker recognition systems in a diffuse noise field

Enhancements to the Generalized Sidelobe Canceller for Audio Beamforming in an Immersive Environment

The Generalized Sidelobe Canceller is an adaptive algorithm for optimally estimating the parameters for beamforming, the signal processing technique of combining data from an array of sensors to improve SNR at a point in space. This work focuses on the algorithm’s application to widely-separated microphone arrays with irregular distributions used for human voice capture. Methods are presented for improving the performance of the algorithm’s blocking matrix, a stage that creates a noise reference for elimination, by proposing a stochastic model for amplitude correction and enhanced use of cross correlation for phase correction and time-difference of arrival estimation via a correlation coefficient threshold. This correlation technique is also applied to a multilateration algorithm for an efficient method of explicit target tracking. In addition, the underlying microphone array geometry is studied with parameters and guidelines for evaluation proposed. Finally, an analysis of the stability of the system is performed with respect to its adaptation parameters

Two-dimensional direction-of-arrival estimation with time-modulated arrays

Two-dimensional direction-of-arrival estimation with time-modulated array

A room acoustics measurement system using non-invasive microphone arrays

This thesis summarises research into adaptive room correction for small rooms and pre-recorded material, for example music of films. A measurement system to predict the sound at a remote location within a room, without a microphone at that location was investigated. This would allow the sound within a room to be adaptively manipulated to ensure that all listeners received optimum sound, therefore increasing their enjoyment. The solution presented used small microphone arrays, mounted on the room's walls. A unique geometry and processing system was designed, incorporating three processing stages, temporal, spatial and spectral. The temporal processing identifies individual reflection arrival times from the recorded data. Spatial processing estimates the angles of arrival of the reflections so that the three-dimensional coordinates of the reflections' origin can be calculated. The spectral processing then estimates the frequency response of the reflection. These estimates allow a mathematical model of the room to be calculated, based on the acoustic measurements made in the actual room. The model can then be used to predict the sound at different locations within the room. A simulated model of a room was produced to allow fast development of algorithms. Measurements in real rooms were then conducted and analysed to verify the theoretical models developed and to aid further development of the system. Results from these measurements and simulations, for each processing stage are presented

HiRIS: an Airborne Sonar Sensor with a 1024 Channel Microphone Array for In-Air Acoustic Imaging

Airborne 3D imaging using ultrasound is a promising sensing modality for robotic applications in harsh environments. Over the last decade, several high-performance systems have been proposed in the literature. Most of these sensors use a reduced aperture microphone array, leading to artifacts in the resulting acoustic images. This paper presents a novel in-air ultrasound sensor that incorporates 1024 microphones, in a 32-by- 32 uniform rectangular array, in combination with a distributed embedded hardware design to perform the data acquisition. Using a broadband Minimum Variance Distortionless Response (MVDR) beamformer with Forward-Backward Spatial Smoothing (FB-SS), the sensor is able to create both 2D and 3D ultrasound images of the full-frontal hemisphere with high angular accuracy with up to 70dB main lobe to side lobe ratio. This paper describes both the hardware infrastructure needed to obtain such highly detailed acoustical images, as well as the signal processing chain needed to convert the raw acoustic data into said images. Utilizing this novel high-resolution ultrasound imaging sensor, we wish to investigate the limits of both passive and active airborne ultrasound sensing by utilizing this virtually artifact-free imaging modality