[pt] O problema de localização de estações móveis pessoais em sistemas celulares de comunicações vem recebendo grande atenção nos últimos anos, tanto por questões ligadas à segurança como por suas amplas aplicações comerciais no desenvolvimento de novos serviços e aplicações. Nesta dissertação foi desenvolvido um ambiente de simulação de localização de estações móveis em ambiente micro celulares empregando um programa de traçado de raios pelo método da força bruta (lançamento de raios), já disponível, para estimar os comprimentos de percursos e tempos de chegada entre diversas estações rádio base e a estação móvel em cenários urbanos modelados por sólidos multifacetados. Os perfis de retardo gerados por este programa são usados como dados de entrada para um programa desenvolvido nesta dissertação que estima a localização dos móveis utilizando os métodos de Taylor e de Chan. O processo desenvolvido foi testado em ambientes de geometria simples fornecendo resultados bastante consistentes e mostrando que a técnica de traçado de raios é uma ferramenta útil para a simulação e desenvolvimento de algoritmos de localização, cujo teste em situações reais exige grande volume de medidas de alta complexidade cujos exemplos na literatura técnica são escassos. Com base nas simulações foi investigadas a influência do número de estações rádio base na precisão das estimativas de localização e realizada uma comparação do desempenho dos métodos em situações com visibilidade (LOS) e sem visibilidade (NLOS). Foi analisado ainda o efeito da altura das estações na precisão dos resultados de localização. / [en] The location of mobile terminals in mobile cellular systems has been receiving increasing attention in the last few years. This interest in focused not only in security aspects but also in the development of new services for commercial application. In this Dissertation a simulation environment for mobile stations location in microcellular systems was developed. The simulation tools include a ray tracing software, previously implemented using the ray launching technique, to estimate the path lengths and time of arrival of signals from the mobile station to several radio base stations, and new software implementing terminal location methods using the Taylor linearization and the Chan methods. The simulation tools were tested in scenarios of simple geometry producing consistent results and showing that ray tracing can be a useful tool for simulation and development of location algorithms. The simulations allowed the investigation of location precision dependence on the number of radio bases employed and the evaluation of the estimation methods in visibility (LOS) and non- visibility (NLOS) conditions. The influence of base station antennas heights was also investigated.

To θέμα του εντοπισμού των κινητών τηλεφώνων έχει τραβήξει την προσοχή τα τελευταία χρόνια εξαιτίας των απαιτήσεων της Ομοσπονδιακής Επιτροπής Επικοινωνιών για το Enhanced 911 η οποία είναι μια υπηρεσία συναγερμού. Τα ασύρματα συστήματα επικοινωνίας 3ης γενιάς ηταν τα πρώτα που υιοθέτησαν στρατηγικές εύρεσης θέσης στα στάνταρντ τους. Στην διαδικασία της εύρεσης της θέσης υπάρχουν 3 βασικές κατηγορίες μετρήσεων που μπορούμε να χρησιμοποιήσουμε. Η πρώτη εκτιμά το κινητό βασίζοντας τις μετρήσεις στην λαμβανόμενη ισχύ σήματος. Η δεύτερη κάνει χρήση των χρόνων άφιξης ή της διαφοράς των χρόνων άφιξης στους σταθμούς βάσης. Η τρίτη κατηγορία έχει να κάνει με τις γωνίες άφιξης στους σταθμούς βάσης. Όλες οι παραπάνω κατηγορίες μετρήσεων υποβαθμίζονται έντονα από την NLOS διάδοση. Η απουσία ενός LOS μονοπατιού μπορεί να βλάψει σημαντικά την εκτίμηση της πραγματικής θέσης του κινητού. Αντικείμενο της παρούσας διπλωματικής είναι η συγκριτική αξιολόγηση και μελέτη κάποιων δημοφιλών τεχνικών εντοπισμού θέσης απλών και υβριδικών κάτω από διαφορετικά ΝLOS περιβάλλοντα και σε συνδυασμό με άλλες εξίσου σημαντικές παραμετρους όπως ειναι το διαθέσιμο πλήθος σταθμών βάσης σε μια περιοχή, η γεωμετρία ή με άλλα λόγια η θέση του κινητού σε σχέση με τους σταθμους βάσης. Προτείνεται επίσης και μια υβριδική τεχνική για την αντιμετώπιση των παραπάνω καταστρεπτικών επιπτώσεων του NLOS φαινομένου. / The problem of mobile location estimation has recently drawn attention due to Federal Communications Commission (FCC) demands of Enhanced-911 (E911) emergency service. Third Generation (3G) wireless systems were the first to adopt location estimation techniques into their standards. There are three basic types of measurements that can be used for location estimation. The first type includes Received Signal Strength measurements. The second type uses Time of Arrival or Time Difference of Arrival measurements of the signal to the base stations. The third type deals with Angle of Arrival measurements of the received signal. The subject of this work is the comparative evaluation and study of certain popular, simple and hybrid location estimation techniques, under different NLOS environments and in conjunction with other equally important parameters such as the number of available base stations, the geometry of the problem and the position of the mobile relative to the base stations. A hybrid method is also suggested for mitigating the destructive consequences of the NLOS effect.

In speech communication systems such as voice-controlled systems, hands-free mobile telephones and hearing aids, the received signals are degraded by room reverberation and background noise. This degradation can reduce the perceived quality and intelligibility of the speech, and decrease the performance of speech enhancement and source localization. These problems are difficult to solve due to the colored and nonstationary nature of the speech signals, and features of the Room Impulse Response (RIR) such as its long duration and non-minimum phase. In this dissertation, we focus on two topics of speech enhancement and speaker localization in noisy reverberant environments. A two-stage speech enhancement method is presented to suppress both early and late reverberation in noisy speech using only one microphone. It is shown that this method works well even in highly reverberant rooms. Experiments under different acoustic conditions confirm that the proposed blind method is superior in terms of reducing early and late reverberation effects and noise compared to other well known single-microphone techniques in the literature. Time Difference Of Arrival (TDOA)-based methods usually provide the most accurate source localization in adverse conditions. The key issue for these methods is to accurately estimate the TDOA using the smallest number of microphones. Two robust Time Delay Estimation (TDE) methods are proposed which use the information from only two microphones. One method is based on adaptive inverse filtering which provides superior performance even in highly reverberant and moderately noisy conditions. It also has negligible failure estimation which makes it a reliable method in realistic environments. This method has high computational complexity due to the estimation in the first stage for the first microphone. As a result, it can not be applied in time-varying environments and real-time applications. Our second method improves this problem by introducing two effective preprocessing stages for the conventional Cross Correlation (CC)-based methods. The results obtained in different noisy reverberant conditions including a real and time-varying environment demonstrate that the proposed methods are superior compared to the conventional TDE methods. / Graduate / 0544 / 0984 / saeed.mosayyebpour@gmail.com

In speech communication systems such as voice-controlled systems, hands-free mobile telephones and hearing aids, the received signals are degraded by room reverberation and background noise. This degradation can reduce the perceived quality and intelligibility of the speech, and decrease the performance of speech enhancement and source localization. These problems are difficult to solve due to the colored and nonstationary nature of the speech signals, and features of the Room Impulse Response (RIR) such as its long duration and non-minimum phase. In this dissertation, we focus on two topics of speech enhancement and speaker localization in noisy reverberant environments. A two-stage speech enhancement method is presented to suppress both early and late reverberation in noisy speech using only one microphone. It is shown that this method works well even in highly reverberant rooms. Experiments under different acoustic conditions confirm that the proposed blind method is superior in terms of reducing early and late reverberation effects and noise compared to other well known single-microphone techniques in the literature. Time Difference Of Arrival (TDOA)-based methods usually provide the most accurate source localization in adverse conditions. The key issue for these methods is to accurately estimate the TDOA using the smallest number of microphones. Two robust Time Delay Estimation (TDE) methods are proposed which use the information from only two microphones. One method is based on adaptive inverse filtering which provides superior performance even in highly reverberant and moderately noisy conditions. It also has negligible failure estimation which makes it a reliable method in realistic environments. This method has high computational complexity due to the estimation in the first stage for the first microphone. As a result, it can not be applied in time-varying environments and real-time applications. Our second method improves this problem by introducing two effective preprocessing stages for the conventional Cross Correlation (CC)-based methods. The results obtained in different noisy reverberant conditions including a real and time-varying environment demonstrate that the proposed methods are superior compared to the conventional TDE methods. / Graduate / 2015-04-23 / 0544 / 0984 / saeed.mosayyebpour@gmail.com

Speech is by far the most natural form of communication between human beings. It is intuitive, expressive and contains information at several cognitive levels. We as humans, are perceptive to several of these cognitive levels of information, as we can gather the information pertaining to the identity of the speaker, the speaker's gender, emotion, location, the language, and so on, in addition to the content of what is being spoken. This makes speech based human machine interaction (HMI), both desirable and challenging for the same set of reasons. For HMI to be natural for humans, it is imperative that a machine understands information present in speech, at least at the level of speaker identity, language, location in space, and the summary of what is being spoken. Although one can draw parallels between the human-human interaction and HMI, the two differ in their purpose. We, as humans, interact with a machine, mostly in the context of getting a task done more efficiently, than is possible without the machine. Thus, typically in HMI, controlling the machine in a specific manner is the primary goal. In this context, it can be argued that, HMI, with a limited vocabulary containing specific commands, would suffice for a more efficient use of the machine. In this thesis, we address the problem of ``Who spoke what and where", in the context of a machine understanding the information pertaining to identities of the speakers, their locations in space and the keywords they spoke, thus considering three levels of information - speaker identity (who), location (where) and keywords (what). This can be addressed with the help of multiple sensors like microphones, video camera, proximity sensors, motion detectors, etc., and combining all these modalities. However, we explore the use of only microphones to address this issue. In practical scenarios, often there are times, wherein, multiple people are talking at the same time. Thus, the goal of this thesis is to detect all the speakers, their keywords, and their locations in mixture signals containing speech from simultaneous speakers. Addressing this problem of ``Who spoke what and where" using only microphone signals, forms a part of acoustic scene analysis (ASA) of speech based acoustic events. We divide the problem of ``who spoke what and where" into two sub-problems: ``Who spoke what?" and ``Who spoke where". Each of these problems is cast in a generic latent variable (LV) framework to capture information in speech at different levels. We associate a LV to represent each of these levels and model the relationship between the levels using conditional dependency. The sub-problem of ``who spoke what" is addressed using single channel microphone signal, by modeling the mixture signal in terms of LV mass functions of speaker identity, the conditional mass function of the keyword spoken given the speaker identity, and a speaker-specific-keyword model. The LV mass functions are estimated in a Maximum likelihood (ML) framework using the Expectation Maximization (EM) algorithm using Student's-t Mixture Model (tMM) as speaker-specific-keyword models. Motivated by HMI in a home environment, we have created our own database. In mixture signals, containing two speakers uttering the keywords simultaneously, the proposed framework achieves an accuracy of 82 % for detecting both the speakers and their respective keywords. The other sub-problem of ``who spoke where?" is addressed in two stages. In the first stage, the enclosure is discretized into sectors. The speakers and the sectors in which they are located are detected in an approach similar to the one employed for ``who spoke what" using signals collected from a Uniform Circular Array (UCA). However, in place of speaker-specific-keyword models, we use tMM based speaker models trained on clean speech, along with a simple Delay and Sum Beamformer (DSB). In the second stage, the speakers are localized within the active sectors using a novel region constrained localization technique based on time difference of arrival (TDOA). Since the problem being addressed is a multi-label classification task, we use the average Hamming score (accuracy) as the performance metric. Although the proposed approach yields an accuracy of 100 % in an anechoic setting for detecting both the speakers and their corresponding sectors in two-speaker mixture signals, the performance degrades to an accuracy of 67 % in a reverberant setting, with a $60$ dB reverberation time (RT60) of 300 ms. To improve the performance under reverberation, prior knowledge of the location of multiple sources is derived using a novel technique derived from geometrical insights into TDOA estimation. With this prior knowledge, the accuracy of the proposed approach improves to 91 %. It is worthwhile to note that, the accuracies are computed for mixture signals containing more than 90 % overlap of competing speakers. The proposed LV framework offers a convenient methodology to represent information at broad levels. In this thesis, we have shown its use with three different levels. This can be extended to several such levels to be applicable for a generic analysis of the acoustic scene consisting of broad levels of events. It will turn out that not all levels are dependent on each other and hence the LV dependencies can be minimized by independence assumption, which will lead to solving several smaller sub-problems, as we have shown above. The LV framework is also attractive to incorporate prior knowledge about the acoustic setting, which is combined with the evidence from the data to derive the information about the presence of an acoustic event. The performance of the framework, is dependent on the choice of stochastic models, which model the likelihood function of the data given the presence of acoustic events. However, it provides an access to compare and contrast the use of different stochastic models for representing the likelihood function.

The goal of this master’s thesis is to explore the possibilities of multichannel localization of acoustic signal sources and their following application on a real signal localization and separation, using Beamforming methods. During this thesis two beamforming methods were selected, namely Delay and Sum a Constant Directivity Beamforming - Circular Arrays, and were applicated on real environment signals using two microphone arrays’ geometries ULA (Uniform linear array) and UCA (Uniform Circular array).

Wide Area Measurements (WAMs) have been widely used in the energy management system (EMS) of power system for monitoring, operation and control. In recent years, the advent of synchronized Phasor Measurements Unit (PMU) has added another dimension to the field of wide-area measurement. However, the high cost of the PMU, which includes the manufacture and deployment fee, is a hurdle to the wide use of the PMU in power systems. Unlike traditional PMUs, the frequency monitoring network (FNET) developed by the Virginia Tech Power IT lab is an Internet—based, GPS—synchronized, wide-area frequency monitoring network deployed at the distribution level, providing a low-cost and easily deployable WAMs solution. In this dissertation, the research work can be categorized into two parts: FNET Design and Situation Awareness Algorithm Development. / Ph. D.

No description available.

This thesis describe detection of direction receiving sound with small–size microphone array. Work is based on analyzing methods of time delay estimation, energy decay or phase difference signal. Work focus mainly on finding of angle of arrival in small time difference. Results of measuring, as programming sound, so sound recorded in laboratory conditions and real enviroment, are mentioned in conclusion. All calculations were done by platform Matlab

Imagine a world where someone’s personal information is constantly compromised, where federal government entities AKA Big Brother always knows what anyone is Googling, who an individual is texting, and their emoticons on Twitter. Government entities have been doing this for years; they never cared if they were breaking the law or their moral compass of human dignity. Every day the Federal government blatantly siphons data with programs from the original ECHELON to the new series like PRISM and Xkeyscore so they can keep their tabs on issues that are none of their business; namely, the personal lives of millions. Our allies are taking note; some are learning our bad habits, from Government Communications Headquarters’ (GCHQ) mass shadowing sharing plan to America’s Russian inspiration, SORM. Some countries are following the United States’ poster child pose of a Brave New World like order of global events. Others like Germany are showing their resolve in their disdain for the rise of tyranny. Soon, these new found surveillance troubles will test the resolve of the American Constitution and its nation’s strong love and tradition of liberty. Courts are currently at work to resolve how current concepts of liberty and privacy apply to the current conditions facing the privacy of society. It remains to be determined how liberty will be affected as well; liberty for the United States of America, for the European Union, the Russian Federation and for the people of the World in regards to the extent of privacy in today’s blurred privacy expectations.