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

Vector sensors for underwater : acoustic communications

Acoustic vector sensors measure acoustic pressure and directional components separately. A claimed advantage of vector sensors over pressure-only arrays is the directional information in a collocated device, making it an attractive option for size-restricted applications. The employment of vector sensors as a receiver for underwater communications is relatively new, where the inherent directionality, usually related to particle velocity, is used for signal-to-noise gain and intersymbol interference mitigation. The fundamental question is how to use vector sensor directional components to bene t communications, which this work seeks to answer and to which it contributes by performing: analysis of acoustic pressure and particle velocity components; comparison of vector sensor receiver structures exploring beamforming and diversity; quanti cation of adapted receiver structures in distinct acoustic scenarios and using di erent types of vector sensors. Analytic expressions are shown for pressure and particle velocity channels, revealing extreme cases of correlation between vector sensors' components. Based on the correlation hypothesis, receiver structures are tested with simulated and experimental data. In a rst approach, called vector sensor passive time-reversal, we take advantage of the channel diversity provided by the inherent directivity of vector sensors' components. In a second approach named vector sensor beam steering, pressure and particle velocity components are combined, resulting in a steered beam for a speci c direction. At last, a joint beam steering and passive time-reversal is proposed, adapted for vector sensors. Tested with two distinct experimental datasets, where vector sensors are either positioned on the bottom or tied to a vessel, a broad performance comparison shows the potential of each receiver structure. Analysis of results suggests that the beam steering structure is preferable for shorter source-receiver ranges, whereas the passive time-reversal is preferable for longer ranges. Results show that the joint beam steering and passive time-reversal is the best option to reduce communication error with robustness along the range.Sensores vetoriais acústicos (em inglês, acoustic vector sensors) são dispositivos que medem, alem da pressão acústica, a velocidade de partícula. Esta ultima, é uma medida que se refere a um eixo, portando, esta associada a uma direção. Ao combinar pressão acústica com componentes de velocidade de partícula pode-se estimar a direção de uma fonte sonora utilizando apenas um sensor vetorial. Na realidade, \um" sensor vetorial é composto de um sensor de pressão (hidrofone) e um ou mais sensores que medem componentes da velocidade de partícula. Como podemos notar, o aspecto inovador está na medição da velocidade de partícula, dado que os hidrofones já são conhecidos.(...)This PhD thesis was supported by the Brazilian Navy Postgraduate Study Abroad Program Port. 227/MB-14/08/2019

3-D Velocity Regulation for Nonholonomic Source Seeking Without Position Measurement

We consider a three-dimensional problem of steering a nonholonomic vehicle to seek an unknown source of a spatially distributed signal field without any position measurement. In the literature, there exists an extremum seeking-based strategy under a constant forward velocity and tunable pitch and yaw velocities. Obviously, the vehicle with a constant forward velocity may exhibit certain overshoots in the seeking process and can not slow down even it approaches the source. To resolve this undesired behavior, this paper proposes a regulation strategy for the forward velocity along with the pitch and yaw velocities. Under such a strategy, the vehicle slows down near the source and stays within a small area as if it comes to a full stop, and controllers for angular velocities become succinct. We prove the local exponential convergence via the averaging technique. Finally, the theoretical results are illustrated with simulations.Comment: submitted to IEEE TCST;12 pages, 10 figure

Localization of radiating sources by an acoustical array

International audienceArrays of sensors are used in many fields to detect signals, to resolve closely spaced targets, to estimate the bearing, the position, the strength and other properties of radiating sources whose signals arrive from different directions. The purpose of the work described in the communication is to provide estimators which are used to localize acoustical sources by an acoustical array of sensors. These estimators are based on acoustic processing algorithms: the conventional beamforming, the Minimum Variance and the constrained Capon algorithm. It is shown that these adaptive algorithms can detect radiating sources which are not detectable by classical weighted arrays of sensors. Numerical results are presented