A study into the design of steerable microphones arrays

Beamforming, being a multi-channel signal processing technique, can offer both spatial and temporal selective filtering. It has much more potential than single channel signal processing in various commercial applications. This thesis presents a study on steerable robust broadband beamformers together with a number of their design formulations. The design formulations allow a simple steering mechanism and yet maintain a frequency invariant property as well as achieve robustness against practical imperfectio

The Capture and Recreation of 3D Auditory Scenes

The main goal of this research is to develop the theory and implement practical tools (in both software and hardware) for the capture and recreation of 3D auditory scenes. Our research is expected to have applications in virtual reality, telepresence, film, music, video games, auditory user interfaces, and sound-based surveillance. The first part of our research is concerned with sound capture via a spherical microphone array. The advantage of this array is that it can be steered into any 3D directions digitally with the same beampattern. We develop design methodologies to achieve flexible microphone layouts, optimal beampattern approximation and robustness constraint. We also design novel hemispherical and circular microphone array layouts for more spatially constrained auditory scenes. Using the captured audio, we then propose a unified and simple approach for recreating them by exploring the reciprocity principle that is satisfied between the two processes. Our approach makes the system easy to build, and practical. Using this approach, we can capture the 3D sound field by a spherical microphone array and recreate it using a spherical loudspeaker array, and ensure that the recreated sound field matches the recorded field up to a high order of spherical harmonics. For some regular or semi-regular microphone layouts, we design an efficient parallel implementation of the multi-directional spherical beamformer by using the rotational symmetries of the beampattern and of the spherical microphone array. This can be implemented in either software or hardware and easily adapted for other regular or semi-regular layouts of microphones. In addition, we extend this approach for headphone-based system. Design examples and simulation results are presented to verify our algorithms. Prototypes are built and tested in real-world auditory scenes

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

Reducing the number of elements in the synthesis of a broadband linear array with multiple simultaneous frequency-invariant beam patterns

© 2018 IEEE. The problem of reducing the number of elements in a broadband linear array with multiple simultaneous crossover frequency-invariant (FI) patterns is considered. Different from the single FI pattern array case, every element channel in the multiple FI pattern array is divided and followed by multiple finite-impulse-response (FIR) filters, and each of the multiple FIR filters has a set of coefficients. In this situation, a collective filter coefficient vector and its energy bound are introduced for each element, and then the problem of reducing the number of elements is transformed as minimizing the number of active collective filter coefficient vectors. In addition, the radiation characteristics including beam pointing direction, mainlobe FI property, sidelobe level, and space-frequency notching requirement for each of the multiple patterns can be formulated as multiple convex constraints. The whole synthesis method is implemented by performing an iterative second-order cone programming (SOCP). This method can be considered as a significant extension of the original SOCP for synthesizing broadband sparse array with single FI pattern. Numerical synthesis results show that the proposed method by synthesizing multiple discretized crossover FI patterns can save more elements than the original iterative SOCP by using a single continuously scannable FI pattern for covering the same space range. Moreover, even for multiple FI-patterns case with complicated space-frequency notching, the proposed method is still effective in the reduction of the number of elements

Wavefield modeling and signal processing for sensor arrays of arbitrary geometry

Sensor arrays and related signal processing methods are key technologies in many areas of engineering including wireless communication systems, radar and sonar as well as in biomedical applications. Sensor arrays are a collection of sensors that are placed at distinct locations in order to sense physical phenomena or synthesize wavefields. Spatial processing from the multichannel output of the sensor array is a typical task. Such processing is useful in areas including wireless communications, radar, surveillance and indoor positioning. In this dissertation, fundamental theory and practical methods of wavefield modeling for radio-frequency array processing applications are developed. Also, computationally-efficient high-resolution and optimal signal processing methods for sensor arrays of arbitrary geometry are proposed. Methods for taking into account array nonidealities are introduced as well. Numerical results illustrating the performance of the proposed methods are given using real-world antenna arrays. Wavefield modeling and manifold separation for vector-fields such as completely polarized electromagnetic wavefields and polarization sensitive arrays are proposed. Wavefield modeling is used for writing the array output in terms of two independent parts, namely the sampling matrix depending on the employed array including nonidealities and the coefficient vector depending on the wavefield. The superexponentially decaying property of the sampling matrix for polarization sensitive arrays is established. Two estimators of the sampling matrix from calibration measurements are proposed and their statistical properties are established. The array processing methods developed in this dissertation concentrate on polarimetric beamforming as well as on high-resolution and optimal azimuth, elevation and polarization parameter estimation. The proposed methods take into account array nonidealities such as mutual coupling, cross-polarization effects and mounting platform reflections. Computationally-efficient solutions based on polynomial rooting techniques and fast Fourier transform are achieved without restricting the proposed methods to regular array geometries. A novel expression for the Cramér-Rao bound in array processing that is tight for real-world arrays with nonidealities in the asymptotic regime is also proposed. A relationship between spherical harmonics and 2-D Fourier basis, called equivalence matrix, is established. A novel fast spherical harmonic transform is proposed, and a one-to-one mapping between spherical harmonic and 2-D Fourier spectra is found. Improvements to the minimum number of samples on the sphere that are needed in order to avoid aliasing are also proposed

The design and implementation of an acoustic phased array transmitter for the demonstration of MIMO techniques

MIMO radar algorithms are the latest generation of techniques that can be applied to array radars. They offer the potential to improve the radar resolution, increase the number of targets that can be identified and give added flexibility in beampattern design. However, little experimental data demonstrating MIMO radar is available because radar arrays are already expensive systems and MIMO extends the com- plexity and cost further. An acoustic array, which works on the same principles as a radio frequency radar array, can be built at a fraction of the cost of a real radar system. The novel contribution of this project was the demonstration ofMIMO radar techniques on an acoustic array, which was designed and built for this purpose. To achieve the project objectives, the theory of traditional phased array radar techniques and MIMO techniques was researched. The phased array and MIMO techniques were also simulated under narrowband and wideband conditions, and the strengths and weaknesses of each were highlighted. This was followed by the design and implementation of a low cost audible acoustic transmitter array to be used with an existing receiver array to demonstrate the investigated array radar techniques. Finally, the techniques were tested on the hardware platform. The simulation and hardware test results were used to evaluate and compare the performance of phased array and MIMO radar techniques. The beampattern design flexibility that is offered by MIMO radar was demonstrated with the transmission and measurement of omnidirectional, single-lobed and multi-lobed MIMO beampat- terns. Also, parameter estimation experiments were performed where phased array and MIMO radar signals were transmitted. Phased array techniques were shown to be simple, effective and robust. The MIMO Capon, APES and GLRT parameter estimation techniques were shown to be sensitive to the type of signals transmitted, and in most cases, the added complexity of these techniques did not lead to improved target parameter estimation results. However, the MIMO technique of transmitter beamforming on reception gave high resolution target range and angle estimates, living up to the expectations placed on MIMO radar

advances in wave digital modeling of linear and nonlinear systems a summary

This brief summarizes some of the main research results that I obtained during the three years, ranging from November 2015 to October 2018, as a Ph.D. student at Politecnico di Milano under the supervision of Professor Augusto Sarti, and that are contained in my doctoral dissertation, entitled "Advances in Wave Digital Modeling of Linear and Nonlinear Systems". The thesis provides contributions to all the main aspects of Wave Digital (WD) modeling of lumped systems: it introduces generalized definitions of wave variables; it presents novel WD models of one- and multi-port linear and nonlinear circuit elements; it discusses systematic techniques for the WD implementation of arbitrary connection networks and it describes a novel iterative method for the implementation of circuits with multiple nonlinear elements. Though WD methods usually focus on the discrete-time implementation of analog audio circuits; the methodologies addressed in the thesis are general enough as to be applicable to whatever system that can be described by an equivalent electric circuit