An antenna array processing system for multiple source bearing estimation

The principal topic of this dissertation is the application of array signal processing to angle-of-arrival (AOA) estimation of multiple plane waves. Assuming that a passive linear array of uniformly spaced sensors is used to measure the radiation field, a digital signal processing system is proposed which determines the number of narrowband sources and their respective bearings;The proposed direction-finding system integrates several algorithms in a cohesive arrangement to exploit their mutually similar structures. The Modified forward-backward linear prediction (MFBLP) spectral analysis method of Tufts and Kumaresan is used to obtain high spatial resolution, and the eigenanalysis which is central to its operation provides an excellent point of entry for a procedure to estimate the number of plane waves detected by the array. This procedure utilizes the AIC or MDL information theoretic criteria in an ensemble manner to generate a reliable estimate of the rank of the signal subspace of the deterministic correlation matrix of the array snapshot;Two algorithms are presented for determining the spatial frequencies of the incoming plane waves, based on the MFBLP method: one uses an iterative version of Newton\u27s method to locate the spectral peaks, and the other uses an iterative method to locate the equivalent complex poles;Statistical processing of the bearing estimates from a number of array snapshots is then used to maintain accuracy and precision in noisy array environment; two different estimators are proposed for this ensemble averaging, and their performance is characterized when applied to a single-source scenario. This utilizes both analytical and Monte Carlo computer simulation. The distributions are characterized in both wavenumber and bearing domains. Expressions for the bearing CRLB, expected standard deviation, and bearing estimate confidence interval are developed, believed to be the first known formulations of overall DF system performance as a function of array spacing, number of elements, true source bearing, and sensor signal-to-noise ratio. The statistical precision is shown to be related to the effective aperture of the antenna array, revealing the degradation in performance as the angle-of-arrival approaches endfire

Narrowband signal processing techniques with applications to distortion product otoacoustic emissions.

by Ma Wing-Kin.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 121-124).Chapter 1 --- Introduction to Otoacoustic Emissions --- p.1Chapter 1.1 --- Introduction --- p.1Chapter 1.2 --- Clinical Significance of the OAEs --- p.2Chapter 1.3 --- Classes of OAEs --- p.3Chapter 1.4 --- The Distortion Product OAEs --- p.4Chapter 1.4.1 --- Measurement of DPOAEs --- p.5Chapter 1.4.2 --- Some Properties of DPOAEs --- p.8Chapter 1.4.3 --- Noise Reduction of DPOAEs --- p.8Chapter 1.5 --- Goal of this work and Organization of the Thesis --- p.9Chapter 2 --- Review to some Topics in Narrowband Signal Estimation --- p.11Chapter 2.1 --- Fourier Transforms --- p.12Chapter 2.2 --- Periodogram ´ؤ Classical Spectrum Estimation Method --- p.15Chapter 2.2.1 --- Signal-to-Noise Ratios and Equivalent Noise Bandwidth --- p.17Chapter 2.2.2 --- Scalloping --- p.18Chapter 2.3 --- Maximum Likelihood Estimation --- p.19Chapter 2.3.1 --- Finding of the ML Estimator --- p.19Chapter 2.3.2 --- Properties of the ML Estimator --- p.21Chapter 3 --- Review to Adaptive Notch/Bandpass Filter --- p.23Chapter 3.1 --- Introduction --- p.23Chapter 3.2 --- Filter Structure --- p.24Chapter 3.3 --- Adaptation Algorithms --- p.25Chapter 3.3.1 --- Least Squares Method --- p.25Chapter 3.3.2 --- Least-Mean-Squares Algorithm --- p.27Chapter 3.3.3 --- Recursive-Least-Squares Algorithm --- p.28Chapter 3.4 --- LMS ANBF Versus RLS ANBF --- p.31Chapter 3.5 --- the IIR filter Versus ANBF --- p.31Chapter 4 --- Fast RLS Adaptive Notch/Bandpass Filter --- p.33Chapter 4.1 --- Motivation --- p.33Chapter 4.2 --- Theoretical Analysis of Sample Autocorrelation Matrix --- p.34Chapter 4.2.1 --- Solution of Φ (n) --- p.34Chapter 4.2.2 --- Approximation of Φ (n) --- p.35Chapter 4.3 --- Fast RLS ANBF Algorithm --- p.37Chapter 4.4 --- Performance Study --- p.39Chapter 4.4.1 --- Relationship to LMS ANBF and Bandwidth Evaluation . --- p.39Chapter 4.4.2 --- Estimation Error of Tap Weights --- p.40Chapter 4.4.3 --- Residual Noise Power of Bandpass Output --- p.42Chapter 4.5 --- Simulation Examples --- p.43Chapter 4.5.1 --- Estimation of Single Sinusoid in Gaussian White Noise . --- p.43Chapter 4.5.2 --- Comparing the Performance of IIR Filter and ANBFs . . --- p.44Chapter 4.5.3 --- Harmonic Signal Enhancement --- p.45Chapter 4.5.4 --- Cancelling 50/60Hz Interference in ECG signal --- p.46Chapter 4.6 --- Simulation Results of Performance Study --- p.52Chapter 4.6.1 --- Bandwidth --- p.52Chapter 4.6.2 --- Estimation Errors --- p.53Chapter 4.7 --- Concluding Summary --- p.55Chapter 4.8 --- Appendix A: Derivation of Ts --- p.56Chapter 4.9 --- Appendix B: Derivation of XT(n)Λ(n)ΛT(n)X(n) --- p.56Chapter 5 --- Investigation of the Performance of two Conventional DPOAE Estimation Methods --- p.58Chapter 5.1 --- Motivation --- p.58Chapter 5.2 --- The DPOAE Signal Model --- p.59Chapter 5.3 --- Preliminaries to the Conventional Methods --- p.60Chapter 5.3.1 --- Conventional Method 1: Constrained Stimulus Generation --- p.60Chapter 5.3.2 --- Conventional Method 2: Windowing --- p.61Chapter 5.4 --- Performance Comparison --- p.63Chapter 5.4.1 --- Sidelobe Level Reduction --- p.63Chapter 5.4.2 --- Estimation Accuracy --- p.65Chapter 5.4.3 --- Noise Floor Level --- p.67Chapter 5.4.4 --- Additional Loss by Scalloping --- p.68Chapter 5.5 --- Simulation Study --- p.69Chapter 5.5.1 --- Sidelobe Suppressions of the Windows --- p.69Chapter 5.5.2 --- Mean Level Estimation --- p.70Chapter 5.5.3 --- Mean Squared Error Analysis --- p.71Chapter 5.6 --- Concluding Summary --- p.75Chapter 5.7 --- Discussion --- p.75Chapter 5.8 --- Appendix A: Cramer-Rao Bound of the DPOAE Level Estimation --- p.76Chapter 6 --- Theoretical Considerations of Maximum Likelihood Estimation for the DPOAEs --- p.77Chapter 6.1 --- Motivation --- p.77Chapter 6.2 --- Finding of the MLEs --- p.78Chapter 6.2.1 --- First Form: Joint Estimation of DPOAE and Artifact Pa- rameter --- p.79Chapter 6.2.2 --- Second Form: Artifact Cancellation --- p.80Chapter 6.3 --- Relationship of CM1 to MLE --- p.81Chapter 6.4 --- Approximating the MLE --- p.82Chapter 6.5 --- Concluding Summary --- p.84Chapter 6.6 --- Appendix A: Equivalent Forms for the Minimum Least Squares Error --- p.85Chapter 7 --- Optimum Estimator Structure and Artifact Cancellation Ap- proaches for the DPOAEs --- p.87Chapter 7.1 --- Motivation --- p.87Chapter 7.2 --- The Optimum Estimator Structure --- p.88Chapter 7.3 --- References and Frequency Offset Effect --- p.89Chapter 7.4 --- Artifact Canceling Algorithms --- p.92Chapter 7.4.1 --- Least-Squares Canceler --- p.93Chapter 7.4.2 --- Windowed-Fourier-Transform Canceler --- p.93Chapter 7.4.3 --- FRLS Adaptive Canceler --- p.95Chapter 7.5 --- Time-domain Noise Rejection --- p.97Chapter 7.6 --- Regional Periodogram --- p.98Chapter 7.7 --- Experimental Results --- p.99Chapter 7.7.1 --- Artifact Cancellation via External Reference --- p.99Chapter 7.7.2 --- Artifact Cancellation via Internal Reference --- p.99Chapter 7.7.3 --- Artifact Cancellation in presence of Transient Noise --- p.101Chapter 7.7.4 --- Illustrative Example: DPgrams --- p.102Chapter 7.8 --- Conclusion and Discussion --- p.111Chapter 7.9 --- Appendix A: Derivation of the Parabolic Interpolation Method . --- p.113Chapter 7.10 --- Appendix B: Derivation of Weighted-Least-Squares Canceler . . --- p.114Chapter 8 --- Conclusions and Future Research Directions --- p.118Chapter 8.1 --- Conclusions --- p.118Chapter 8.2 --- Future Research Directions --- p.119Bibliography --- p.12

Improving robustness of continuous-gravitational-wave searches against signal-like instrumental artefacts and a concept for an octahedral gravitational-wave detector in space

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A wide area system for power transmission security enhancement using a process systems approach

Imperial Users onl

Linear Predictive Spectral Analysis via the Lp Norm

This study involves linear predictive spectral analysis under the general LP norm; both one dimensional and two dimensional spectral estimation algorithms are developed. The objective in this study is determination of frequency resolution capability for various LP normed solutions to linear predictive spectral estimation equations. A modified residual steepest descent algorithm is utilized to generate the required solution. The research presented in this thesis could not have been accomplished without the support of the Oklahoma State University Research Consortium For Well Log Data Enhancement Via Signal Processing. The member companies of this consortium include Amococ Production Company, Area Oil and Gas Company, Cities Service Oil and Gas Corporation, Conoco, Exxon, IBM, Mobil Research and Development, Phillips Petroleum Corporation, Sohio Petroleum Company, and Texaco.Electrical Engineerin

MTF for Photographic Films by Parameter Estimation in the Space and Frequency Domains

A new method for determining the modulation transfer function (MTF) for photographic films is described. The MTF and corresponding line spread function are approximated by carefully chosen models which are uniquely specified by a few parametric constants. By estimating the parameters in space and frequency simultaneously, the interactions between the two domains result in improved estimates over those provided by either domain alone. A computer algorithm has been written to determine the parameter constants that define the best-fit model for the emulsion MTF

Phase-Distortion-Robust Voice-Source Analysis

This work concerns itself with the analysis of voiced speech signals, in particular the analysis of the glottal source signal. Following the source-filter theory of speech, the glottal signal is produced by the vibratory behaviour of the vocal folds and is modulated by the resonances of the vocal tract and radiation characteristic of the lips to form the speech signal. As it is thought that the glottal source signal contributes much of the non-linguistic and prosodical information to speech, it is useful to develop techniques which can estimate and parameterise this signal accurately. Because of vocal tract modulation, estimating the glottal source waveform from the speech signal is a blind deconvolution problem which necessarily makes assumptions about the characteristics of both the glottal source and vocal tract. A common assumption is that the glottal signal and/or vocal tract can be approximated by a parametric model. Other assumptions include the causality of the speech signal: the vocal tract is assumed to be a minimum phase system while the glottal source is assumed to exhibit mixed phase characteristics. However, as the literature review within this thesis will show, the error criteria utilised to determine the parameters are not robust to the conditions under which the speech signal is recorded, and are particularly degraded in the common scenario where low frequency phase distortion is introduced. Those that are robust to this type of distortion are not well suited to the analysis of real-world signals. This research proposes a voice-source estimation and parameterisation technique, called the Power-spectrum-based determination of the Rd parameter (PowRd) method. Illustrated by theory and demonstrated by experiment, the new technique is robust to the time placement of the analysis frame and phase issues that are generally encountered during recording. The method assumes that the derivative glottal flow signal is approximated by the transformed Liljencrants-Fant model and that the vocal tract can be represented by an all-pole filter. Unlike many existing glottal source estimation methods, the PowRd method employs a new error criterion to optimise the parameters which is also suitable to determine the optimal vocal-tract filter order. In addition to the issue of glottal source parameterisation, nonlinear phase recording conditions can also adversely affect the results of other speech processing tasks such as the estimation of the instant of glottal closure. In this thesis, a new glottal closing instant estimation algorithm is proposed which incorporates elements from the state-of-the-art techniques and is specifically designed for operation upon speech recorded under nonlinear phase conditions. The new method, called the Fundamental RESidual Search or FRESS algorithm, is shown to estimate the glottal closing instant of voiced speech with superior precision and comparable accuracy as other existing methods over a large database of real speech signals under real and simulated recording conditions. An application of the proposed glottal source parameterisation method and glottal closing instant detection algorithm is a system which can analyse and re-synthesise voiced speech signals. This thesis describes perceptual experiments which show that, iunder linear and nonlinear recording conditions, the system produces synthetic speech which is generally preferred to speech synthesised based upon a state-of-the-art timedomain- based parameterisation technique. In sum, this work represents a movement towards flexible and robust voice-source analysis, with potential for a wide range of applications including speech analysis, modification and synthesis

Probability of detection analysis for infrared nondestructive testing and evaluation with applications including a comparison with ultrasonic testing

La fiabilité d'une technique d’Évaluation Non-Destructive (END) est l'un des aspects les plus importants dans la procédure globale de contrôle industriel. La courbe de la Probabilité de Détection (PdD) est la mesure quantitative de la fiabilité acceptée en END. Celle-ci est habituellement exprimée en fonction de la taille du défaut. Chaque expérience de fiabilité en END devrait être bien conçue pour obtenir l'ensemble de données avec une source valide, y compris la technique de Thermographie Infrarouge (TI). La gamme des valeurs du rapport de l'aspect de défaut (Dimension / profondeur) est conçue selon nos expériences expérimentales afin d’assurer qu’elle vient du rapport d’aspect non détectable jusqu’à celui-ci soit détectable au minimum et plus large ensuite. Un test préliminaire est mis en œuvre pour choisir les meilleurs paramètres de contrôle, telles que l'énergie de chauffage, le temps d'acquisition et la fréquence. Pendant le processus de traitement des images et des données, plusieurs paramètres importants influent les résultats obtenus et sont également décrits. Pour la TI active, il existe diverses sources de chauffage (optique ou ultrason), des formes différentes de chauffage (pulsé ou modulé, ainsi que des méthodes différentes de traitement des données. Diverses approches de chauffage et de traitement des données produisent des résultats d'inspection divers. Dans cette recherche, les techniques de Thermographie Pulsée (TP) et Thermographie Modulée(TM) seront impliquées dans l'analyse de PdD. Pour la TP, des courbes PdD selon différentes méthodes de traitement de données sont comparées, y compris la Transformation de Fourier, la Reconstruction du Signal thermique, la Transformation en Ondelettes, le Contraste Absolu Différentiel et les Composantes Principales en Thermographie. Des études systématiques sur l'analyse PdD pour la technique de TI sont effectuées. Par ailleurs, les courbes de PdD en TI sont comparées avec celles obtenues par d'autres approches traditionnelles d’END.The reliability of a Non-Destructive Testing and Evaluation (NDT& E) technique is one of the most important aspects of the overall industrial inspection procedure. The Probability of Detection (PoD) curve is the accepted quantitative measure of the NDT& E reliability, which is usually expressed as a function of flaw size. Every reliability experiment of the NDT& E system must be well designed to obtain a valid source data set, including the infrared thermography (IRT) technique. The range of defect aspect ratio (Dimension / depth) values is designed according to our experimental experiences to make sure it is from non-detectable to minimum detectable aspect ratio and larger. A preliminary test will be implemented to choose the best inspection parameters, such as heating energy, the acquisition time and frequency. In the data and image processing procedure, several important parameters which influence the results obtained are also described. For active IRT, there are different heating sources (optical or ultrasound), heating forms (pulsed or lock-in) and also data processing methods. Distinct heating and data processing manipulations produce different inspection results. In this research, both optical Pulsed Thermography (PT) and Lock-in Thermography (LT) techniques will be involved in the PoD analysis. For PT, PoD curves of different data processing methods are compared, including Fourier Transform (FT), 1st Derivative (1st D) after Thermal Signal Reconstruction (TSR), Wavelet Transform (WT), Differential Absolute Contrast (DAC), and Principal Component Thermography (PCT). Systematic studies on PoD analysis for IRT technique are carried out. Additionally, constructed PoD curves of IRT technique are compared with those obtained by other traditional NDT& E approaches

Toward a mathematical theory of perception

A new technique for the modelling of perceptual systems called formal modelling is developed. This technique begins with qualitative observations about the perceptual system, the so-called perceptual symmetries, to obtain through mathematical analysis certain model structures which may then be calibrated by experiment. The analysis proceeds in two different ways depending upon the choice of linear or nonlinear models. For the linear case, the analysis proceeds through the methods of unitary representation theory. It begins with a unitary group representation on the image space and produces what we have called the fundamental structure theorem. For the nonlinear case, the analysis makes essential use of infinite-dimensional manifold theory. It begins with a Lie group action on an image manifold and produces the fundamental structure formula. These techniques will be used to study the brightness perception mechanism of the human visual system. Several visual groups are defined and their corresponding structures for visual system models are obtained. A new transform called the Mandala transform will be deduced from a certain visual group and its implications for image processing will be discussed. Several new phenomena of brightness perception will be presented. New facts about the Mach band illusion along with new adaptation phenomena will be presented. Also a new visual illusion will be presented. A visual model based on the above techniques will be presented. It will also be shown how use of statistical estimation theory can be made in the study of contrast adaptation. Furthermore, a mathematical interpretation of unconscious inference and a simple explanation of the Tolhurst effect without mutual channel inhibition will be given. Finally, image processing algorithms suggested by the model will be used to process a real-world image for enhancement and for "form" and texture extraction