Beamforming in near-field - metaheuristic approach and experimental tests in an anechoic chamber

A set of microphones spatially arranged in space in a specific pattern is called a microphone array. It can be used to extract and enhance the signal of interest from its observation corrupted by other interfering signals, such as noise or to estimate the direction of arrival of a source. In this paper we focus on a problem in which the desired signal (speech signal) is interfered by other signal with fully overlapping bandwidth but with different localization. Our goal is to attenuate the interfering signal. We experimentally study the method in which microphones do not have to be equally spaced and all information regarding signal phase is hidden in a transfer function of the microphone. We focus on determining the microphones positions and FIR filter coefficients so that the actual output the beamformer is as close as possible to the desired one (the level of speech signal remains unchanged, while the interfering signal is attenuated) in the sense of  norm. To solve this problem, we use a metaheuristic algorithm. Next, we construct the array and make an experiment in anechoic chamber. The initial results of the experiment show that the proposed method can be applied for array designing

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

On the sparse beamformer design

In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation. Moreover, the size of the array can also be pruned to reduce complexity. These problems are addressed in this paper. A suitable optimization model is proposed. Both array pruning and filter thinning can be solved together as a two-stage optimization problem to yield the final sparse designs. Numerical results show that the complexity of the designed beamformers can be reduced significantly with minimal effect on performance

Array signal processing for source localization and enhancement

“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

Active control of noise transmitted from barriers

Active noise cancellation is a unique approach that helps passive noise control in reducing sound levels at low frequencies; nevertheless, successful use of active noise cancellation necessitates performing numerous and tedious experiments together with defining several parameters properly. The locations and quantity of active control system transducers are among these parameters. The present research provides a comprehensive framework for placing control sources and error microphones near a noise barrier in order to improve its efficiency in both narrowband and broadband noise spectra. To accomplish this, the appropriate locations for the control sources are first determined using a repetitive computation method, and then the optimizations are completed by determining the best position for the error microphone. Several alternative transducer locations near the barrier are incorporated in the repetitive computation, and the optimal sites for the control sources and error microphones are found using two-step optimization methods as well as the genetic algorithms approach. The findings reveal that the best places to put the control sources are on the incident side, below the barrier's edge, and the best locations to place the error microphones are on the shadow side, as close as possible to the target area. The effect of ground reflection on the efficiency of the active noise control system is also investigated, and it is discovered that while ground reflection has no significant effect on the performance of the active noise control system for broadband frequency ranges, it does reduce the control system's efficiency at tonal noises. In order to optimize more parameters, further calculations are performed based on the genetic optimizer. The output of the GA calculations found new configurations for the control units that result in higher noise level reduction at the target area. In addition to the active noise barrier, the application of active noise cancellation for open windows as a particular case of the barrier is explored as a particular case of the barrier. Different arrangements are studied for the control units close to the open windows, including linear, boundary, and planar control arrangements. The effect of several parameters such as the incident angle of noise waves, the distance between error microphones and the opening, and the number of control units are investigated. The results demonstrate that the active noise control system with obliqued linear placements of transducers have higher performance than the other arrangements. Furthermore, when the frequency and incident angle increase, the effectiveness of active noise reduction decreases.La cancelación activa de ruido es un enfoque único que ayuda al control pasivo del ruido a reducir los niveles de sonido a bajas frecuencias; sin embargo, el uso exitoso de la cancelación activa de ruido requiere la realización de numerosos y tediosos experimentos junto con la definición adecuada de varios parámetros. La ubicación y la cantidad de transductores del sistema de control activo se encuentran entre estos parámetros. La presente investigación proporciona un marco completo para colocar fuentes de control y micrófonos de error cerca de una barrera de ruido con el fin de mejorar su eficiencia en espectros de ruido de banda estrecha y banda ancha. Para lograr esto, primero se determinan las ubicaciones apropiadas para las fuentes de control usando un método de cálculo repetitivo, y luego se completan las optimizaciones determinando la mejor posición para el micrófono de error. Varias ubicaciones de transductores alternativas cerca de la barrera se incorporan en el cálculo repetitivo, y los sitios óptimos para las fuentes de control y los micrófonos de error se encuentran utilizando métodos de optimización de dos pasos, así como el enfoque de algoritmos genéticos. Los hallazgos revelan que los mejores lugares para colocar las fuentes de control están en el lado del incidente, debajo del borde de la barrera, y los mejores lugares para colocar los micrófonos de error están en el lado de la sombra, lo más cerca posible del área objetivo. También se investiga el efecto de la reflexión del suelo sobre la eficiencia del sistema de control de ruido activo, y se descubre que si bien la reflexión del suelo no tiene un efecto significativo en el rendimiento del sistema de control de ruido activo para rangos de frecuencia de banda ancha, sí reduce el rendimiento del sistema de control. eficiencia en ruidos tonales. Para optimizar más parámetros, se realizan más cálculos basadosen el optimizador genético. El resultado de los cálculos de GA encontró nuevas configuraciones para las unidades de control que dan como resultado una mayor reducción del nivel de ruido en el área objetivo. Además de la barrera de ruido activa, se explora la aplicación de la cancelación de ruido activa para ventanas abiertas como un caso particular de la barrera. Se estudian cuatro disposiciones para las unidades de control cercanas a las ventanas abiertas. Las unidades de control en una configuración de límite se colocan en el borde de la abertura, mientras que en el control plano, se ubican en la superficie de la abertura. En una configuración de contorno, las unidades de control se colocan en el borde de la abertura, mientras que en un diseño plano, se colocan en la superficie de la abertura. Se investiga el efecto de varios parámetros como el ángulo de incidencia de las ondas de ruido, la distancia entre los micrófonos de error y la apertura, y el número de unidades de control. Los resultados demuestran que el sistema de control de ruido activo con configuración plana tiene un rendimiento más alto que el control de límites. Además, cuando la frecuencia y el ángulo de incidencia aumentan, la eficacia de la reducción activa del ruido disminuye.Postprint (published version

Applications and enhancements of aircraft design optimization techniques

The aircraft industry has been at the forefront in developing design optimization strategies ever since the advent of high performance computing. Thanks to the large computational resources now available, many new as well as more mature optimization methods have become well established. However, the same cannot be said for other stages along the optimization process - chiefly, and this is where the present thesis seeks to make its first main contribution, at the geometry parameterization stage.The first major part of the thesis is dedicated to the goal of reducing the size of the search space by reducing the dimensionality of existing parameterization schemes, thus improving the effectiveness of search strategies based upon them. Specifically, a refinement to the Kulfan parameterization method is presented, based on using Genetic Programming and a local search within a Baldwinian learning strategy to evolve a set of analytical expressions to replace the standard 'class function' at the basis of the Kulfan method. The method is shown to significantly reduce the number of parameters and improves optimization performance - this is demonstrated using a simple aerodynamic design case study.The second part describes an industrial level case study, combining sophisticated, high fidelity, as well as fast, low fidelity numerical analysis with a complex physical experiment. The objective is the analysis of a topical design question relating to reducing the environmental impact of aviation: what is the optimum layout of an over-the-wing turbofan engine installation designed to enable the airframe to shield near-airport communities on the ground from fan noise. An experiment in an anechoic chamber reveals that a simple half-barrier noise model can be used as a first order approximation to the change of inlet broadband noise shielding by the airframe with engine position, which can be used within design activities. Moreover, the experimental results are condensed into an acoustic shielding performance metric to be used in a Multidisciplinary Design Optimization study, together with drag and engine performance values acquired through CFD. By using surrogate models of these three performance metrics we are able to find a set of non-dominated engine positions comprising a Pareto Front of these objectives. This may give designers of future aircraft an insight into an appropriate engine position above a wing, as well as a template for blending multiple levels of computational analysis with physical experiments into a multidisciplinary design optimization framework