Constant-pressure sound waves in non-Hermitian disordered media

When waves impinge on a disordered material they are back-scattered and form a highly complex interference pattern. Suppressing any such distortions in the free propagation of a wave is a challenging task with many applications in a number of different disciplines. In a recent theoretical proposal, it was pointed out that both perfect transmission through disorder as well as a complete suppression of any variation in a wave intensity can be achieved by adding a continuous gain-loss distribution to the disorder. Here we show that this abstract concept can be implemented in a realistic acoustic system. Our prototype consists of an acoustic waveguide containing several inclusions that scatter the incoming wave in a passive configuration and provide the gain or loss when being actively controlled. Our measurements on this non-Hermitian acoustic metamaterial demonstrate unambiguously the creation of a reflectionless scattering wave state that features a unique form of discrete constant-amplitude pressure waves. In addition to demonstrating that gain-loss additions can turn localised systems into transparent ones, we expect our proof-of-principle demonstration to trigger interesting new developments not only in sound engineering, but also in other related fields such as in non-Hermitian photonics

Source Localisation in Wireless Sensor Networks Based on Optimised Maximum Likelihood

Maximum likelihood (ML) is a popular and effective estimator for a wide range of diverse applications and currently affords the most accurate estimation for source localisation in wireless sensor networks (WSN). ML however has two major shortcomings namely, that it is a biased estimator and is also highly sensitive to parameter perturbations. An Optimisation to ML (OML) algorithm was introduced that minimises the sum-of-squares bias and exhibits superior performance to ML in statistical estimation, particularly with finite datasets. This paper proposes a new model for acoustic source localisation in WSN, based upon the OML estimation process. In addition to the performance analysis using real world field experimental data for the tracking of moving military vehicles, simulations have been performed upon the more complex source localisation and tracking problem, to verify the potential of the new OML-based model

Visual / acoustic detection and localisation in embedded systems

©Cranfield UniversityThe continuous miniaturisation of sensing and processing technologies is increasingly offering a variety of embedded platforms, enabling the accomplishment of a broad range of tasks using such systems. Motivated by these advances, this thesis investigates embedded detection and localisation solutions using vision and acoustic sensors. Focus is particularly placed on surveillance applications using sensor networks. Existing vision-based detection solutions for embedded systems suffer from the sensitivity to environmental conditions. In the literature, there seems to be no algorithm able to simultaneously tackle all the challenges inherent to real-world videos. Regarding the acoustic modality, many research works have investigated acoustic source localisation solutions in distributed sensor networks. Nevertheless, it is still a challenging task to develop an ecient algorithm that deals with the experimental issues, to approach the performance required by these systems and to perform the data processing in a distributed and robust manner. The movement of scene objects is generally accompanied with sound emissions with features that vary from an environment to another. Therefore, considering the combination of the visual and acoustic modalities would offer a significant opportunity for improving the detection and/or localisation using the described platforms. In the light of the described framework, we investigate in the first part of the thesis the use of a cost-effective visual based method that can deal robustly with the issue of motion detection in static, dynamic and moving background conditions. For motion detection in static and dynamic backgrounds, we present the development and the performance analysis of a spatio- temporal form of the Gaussian mixture model. On the other hand, the problem of motion detection in moving backgrounds is addressed by accounting for registration errors in the captured images. By adopting a robust optimisation technique that takes into account the uncertainty about the visual measurements, we show that high detection accuracy can be achieved. In the second part of this thesis, we investigate solutions to the problem of acoustic source localisation using a trust region based optimisation technique. The proposed method shows an overall higher accuracy and convergence improvement compared to a linear-search based method. More importantly, we show that through characterising the errors in measurements, which is a common problem for such platforms, higher accuracy in the localisation can be attained. The last part of this work studies the different possibilities of combining visual and acoustic information in a distributed sensors network. In this context, we first propose to include the acoustic information in the visual model. The obtained new augmented model provides promising improvements in the detection and localisation processes. The second investigated solution consists in the fusion of the measurements coming from the different sensors. An evaluation of the accuracy of localisation and tracking using a centralised/decentralised architecture is conducted in various scenarios and experimental conditions. Results have shown the capability of this fusion approach to yield higher accuracy in the localisation and tracking of an active acoustic source than by using a single type of data

An Online Solution for Localisation, Tracking and Separation of Moving Speech Sources

The problem of separating a time varying number of speech sources in a room is difficult to solve. The challenge lies in estimating the number and the location of these speech sources. Furthermore, the tracked speech sources need to be separated. This thesis proposes a solution which utilises the Random Finite Set approach to estimate the number and location of these speech sources and subsequently separate the speech source mixture via time frequency masking

The significance of passive acoustic array-configurations on sperm whale range estimation when using the hyperbolic algorithm

In cetacean monitoring for population estimation, behavioural studies or mitigation, traditional visual observations are being augmented by the use of Passive Acoustic Monitoring (PAM) techniques that use the creature’s vocalisations for localisation. The design of hydrophone configurations is evaluated for sperm whale (Physeter macrocephalus) range estimation to meet the requirements of the current mitigation regulations for a safety zone and behaviour research. This thesis uses the Time Difference of Arrival (TDOA) of cetacean vocalisations with a three-dimensional hyperbolic localisation algorithm. A MATLAB simulator has been developed to model array-configurations and to assess their performance in source range estimation for both homogeneous and non-homogeneous sound speed profiles (SSP). The non-homogeneous medium is modelled on a Bellhop ray trace model, using data collected from the Gulf of Mexico. The sperm whale clicks are chosen as an exemplar of a distinctive underwater sound. The simulator is tested with a separate synthetic source generator which produced a set of TDOAs from a known source location. The performance in source range estimation for Square, Trapezium, Triangular, Shifted-pair and Y-shape geometries is tested. The Y-shape geometry, with four elements and aperture-length of 120m, is the most accurate, giving an error of ±10m over slant ranges of 500m in a homogeneous medium, and 300m in a non-homogeneous medium. However, for towed array deployments, the Y-shape array is sensitive to angle-positioning-error when the geometry is seriously distorted. The Shifted-pair geometry overcomes these limits, performing an initial accuracy of ±30m when the vessel either moves in a straight line or turns to port or starboard. It constitutes a recommendable array-configuration for towed array deployments. The thesis demonstrates that the number of receivers, the array-geometry and the arrayaperture are important parameters to consider when designing and deploying a hydrophone array. It is shown that certain array-configurations can significantly improve the accuracy of source range estimation. Recommendations are made concerning preferred array-configurations for use with PAM systems

Time resolved tracking of a sound scatterer in a turbulent flow: non-stationary signal analysis and applications

It is known that ultrasound techniques yield non-intrusive measurements of hydrodynamic flows. For example, the study of the echoes produced by a large number of particle insonified by pulsed wavetrains has led to a now standard velocimetry technique. In this paper, we propose to extend the method to the continuous tracking of one single particle embedded in a complex flow. This gives a Lagrangian measurement of the fluid motion, which is of importance in mixing and turbulence studies. The method relies on the ability to resolve in time the Doppler shift of the sound scattered by the continuously insonfied particle. For this signal processing problem two classes of approaches are used: time-frequency analysis and parametric high resolution methods. In the first class we consider the spectrogram and reassigned spectrogram, and we apply it to detect the motion of a small bead settling in a fluid at rest. In more non-stationary turbulent flows where methods in the second class are more robust, we have adapted an Approximated Maximum Likelihood technique coupled with a generalized Kalman filter.Comment: 16 pages 9 figure