Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2018-05-29T12:47:57Z No. of bitstreams: 2 Dissertação - André Almeida Souza Coelho - 2018.pdf: 12771064 bytes, checksum: b6418151bb082eeffbdb1692392e483e (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-05-29T12:49:33Z (GMT) No. of bitstreams: 2 Dissertação - André Almeida Souza Coelho - 2018.pdf: 12771064 bytes, checksum: b6418151bb082eeffbdb1692392e483e (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-05-29T12:49:33Z (GMT). No. of bitstreams: 2 Dissertação - André Almeida Souza Coelho - 2018.pdf: 12771064 bytes, checksum: b6418151bb082eeffbdb1692392e483e (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-19 / This work deals with the problem of estimation of incident angles (DOA) of plane waves on a linear array of sensors taking into account the mutual coupling between the sensors. MUSIC and SEAD methods are analyzed with and without coupling, in the cases of correlated and uncorrelated signals, and a compensation method is applied to minimize estimation errors. Several results are obtained and the statistical performance of MUSIC and SEAD is evaluated, proposing an application scenario for SEAD when under the influence of mutual coupling between the sensors. / Este trabalho aborda o problema de estimação de ângulos de incidência (DOA) de ondas planas sobre um arranjo linear de sensores levando em consideração o acoplamento mútuo entre os sensores. São analisados os métodos MUSIC e SEAD com e sem acoplamento, nos casos de sinais descorrelacionados e correlacionados, e aplicado um método de compensação para minimizar os erros de estimação. Diversos resultados são obtidos e o desempenho estatístico do MUSIC e SEAD é avaliado, propondo um cenário de aplicação para o SEAD quando sob a influência do acoplamento mútuo entre os sensores.

This diploma thesis deals with DOA organization in the environment of Brno University of Technology. Its aim is a research of regulatory requirements for the DOA; to propose a procedure for obtaining Design Organization Approval and a summary of information about necessary staffing.

Cette thèse porte sur la localisation de sources spatialement distribuées. Premièrement, des résultats théoriques ont été établis concernant les performances des méthodes à haute résolution en présence d'erreurs de modèle dues à la distribution angulaire de source. Ainsi, le biais d'estimation et l'erreur quadratique moyenne sont exprimées en fonction des paramètres liés à l'erreur de modèle. De plus, les performances ont été étudiées en fonction de la géométrie de l'antenne afin de déterminer les configurations les plus robustes aux sources dispersées.Les résultats théoriques ont été validés par des simulations numériques. Dans un deuxième temps, une nouvelle approche non paramétrique a été proposée pour la localisation de sources distribuées : cette approche exploite les propriétés de parcimonie et de rang-faible de la matrice de covariance spatiale des sources. Cette méthode permet en outre d'estimer la forme de la distribution spatiale des sources. Les résultats de simulations ont permis de mettre en avant l'intérêt de l'hypothèse rang faible par rapport aux critères exploitant uniquement la parcimonie / This thesis focuses on the distributed source localization problem. In a first step, performance of high resolution methods in the presence of model errors due to the angular distribution of source has been studied. Theoretical expressions of the estimation bias and the mean square error of the direction of arrival of sources have been established in terms of model error. The impacts of the array geometry on the performances have studied in order to optimize the robustness of the array to the model error due to distributed sources.Theoretical results have been validated by numerical simulations.In a second step, a new approach for the localization of spatially distributed source has been proposed: the approach is based on the sparsity and low-rank property of the spatial covariance matrix of the sources. The proposed method provides also an estimation of the distribution shapes of the sources. Simulation results exhibit the advantages of exploiting the sparsity and the low rank properties.

In this dissertation, sparse processing of signals for directions-of-arrival (DoAs) estimation is addressed in the framework of Compressive Sensing (CS). In particular, DoAs estimation problem for different types of sources, systems, and applications are formulated in the CS paradigm. In addition, the fundamental conditions related to the ``Sparsity'' and ``Linearity'' are carefully exploited in order to apply confidently the CS-based methodologies. Moreover, innovative strategies for various systems and applications are developed, validated numerically, and analyzed extensively for different scenarios including signal to noise ratio (SNR), mutual coupling, and polarization loss. The more realistic data from electromagnetic (EM) simulators are often considered for various analysis to validate the potentialities of the proposed approaches. The performances of the proposed estimators are analyzed in terms of standard root-mean-square error (RMSE) with respect to different degrees-of-freedom (DoFs) of DoAs estimation problem including number of elements, number of signals, and signal properties. The outcomes reported in this thesis suggest that the proposed estimators are computationally efficient (i.e., appropriate for real time estimations), robust (i.e., appropriate for different heterogeneous scenarios), and versatile (i.e., easily adaptable for different systems).

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2018-08-13T14:49:42Z No. of bitstreams: 2 Dissertação - Lucas Fiorini Cruz - 2018.pdf: 23542908 bytes, checksum: 75e04989d0719a9b5d0d22225c38ce7a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-08-14T11:35:12Z (GMT) No. of bitstreams: 2 Dissertação - Lucas Fiorini Cruz - 2018.pdf: 23542908 bytes, checksum: 75e04989d0719a9b5d0d22225c38ce7a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-08-14T11:35:12Z (GMT). No. of bitstreams: 2 Dissertação - Lucas Fiorini Cruz - 2018.pdf: 23542908 bytes, checksum: 75e04989d0719a9b5d0d22225c38ce7a (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-05-18 / Electroencephalography (EEG) measurements are widely used in clinical assessments for research due to its noninvasive nature and for providing several informations on the neural activity associated to both neural functions and disorders, including epilepsy syndromes. In cases related with partial epilepsy, surgical interventions are recommended and the accurate location of the seizure becomes a sine qua non prerequisite for those procedures. Brain source position estimation can help in the selection and classification of brain spots. In this sense, for control purposes, this work begins with the development of a mathematical model that is more electromagnetically representative than the usual model, presenting different aggregate characteristics such as refraction and, especially, frequency dependent attenuation of the wave. We also propose a new method that estimates the source positions from spectral peaks produced by the eigenvalues of the sum of the spatial covariance matrix of the EEG signals and a spatial covariance matrix related to a simulated source that is numerically swept throughout every point on different horizontal layers of the brain. The key approach was to select the eigenvalues that were less affected by the noise and use them to produce the search spectrum. In order to assess the accuracy and robustness of the proposed method, we compared its RMSE (Root Mean Square Error) performance at different SNRs (Signal-to-Noise Ratio) to those of MUSIC (Multiple Signal Classification), a method based on orthogonal subspaces, and NSF (Noise Subspace Fitting), a method based on subspace fitting. The results were produced for both the usual and proposed signal model in order to evaluate their accuracy. Subsequently, the signal models were compared after spatial filtering, aiming the determination of the waveform of a particular source. The proposed approach presents the lowest threshold SNR and the highest accuracy under noisy conditions for all analyzed cases and for both models. The new approach for the signal model made the estimation more accurate in all the studied cases, besides providing greater accuracy on spatial filtering, when compared to the usual model. / Sinais de eletroencefalografia (EEG) são amplamente utilizados em análises clínicas e para fins de pesquisas devido ao seu caráter não invasivo e por possuírem informações sobre as atividades neurais ligadas às funções e anomalias cerebrais, incluindo a epilepsia. Nos casos relacionados à epilepsia parcial, intervenções cirúrgicas são recomendadas e a precisa localização da região epileptogênica é uma condição sine qua non para tal procedimento. Nesse sentido, para fins de controle, este trabalho se inicia com a proposta de um novo modelo matemático das atividades elétricas do cérebro que, quando comparado ao modelo Dipolo elétrico - encontrado na literatura - aproxima-se mais do real, apresentando diferentes características agregadas como refração e, especialmente, atenuação dependente da frequência da onda. Em outro plano, também é proposto um novo método que estima as posições das fontes elétricas cerebrais a partir de picos espectrais produzidos por autovalores da soma da matriz de covariância espacial do sinal EEG com uma matriz de covariância espacial relacionada a uma fonte simulada que, numericamente, é posicionada em pontos de diferentes camadas horizontais do cérebro. A chave para essa abordagem é selecionar os autovalores menos afetados pelo ruído e utilizá-los para construir o espectro de busca. Para analisar a robustez e acurácia do método, avalia-se o seu desempenho em relação à raiz do erro médio quadrático (REMQ) para diferentes valores de relação sinal-ruído (SNR), comparando-o ao algoritmo MUSIC (Multiple Signal Classification), baseado em subespaços ortogonais, e ao NSF (Noise Subspace Fitting), método baseado em “distância” entre subespaços (subspace fitting). Todos os resultados são gerados para o modelo de sinal usual e o proposto, com fim de avaliar a acurácia conferida a cada um destes. Posteriormente, os modelos de sinal são comparados quanto à filtragem espacial, buscando a determinação da forma de onda de uma fonte em particular. A abordagem proposta apresenta uma menor SNR de limiar de desempenho e uma maior acurácia sob condições ruidosas em todos os casos analisados e nos dois modelos. O novo modelo do sinal tornou a estimação DOA mais precisa em todos os casos estudados, além de ter conferido maior precisão à filtragem espacial, quando comparado ao modelo usual.

Un radar MIMO (Multiple Input Multiple Output) est un système radar qui utilise plusieurs antennes émettrices et réceptrices, dans lequel les formes d'ondes émises peuvent être indépendantes. Par rapport aux radars utilisant des antennes en réseaux phasés, les radars MIMO offrent davantage de degrés de liberté, ce qui permet d'améliorer les performances du système en termes de détection et localisation. La technique MIMO offre également la possibilité de synthétiser un diagramme de rayonnement désiré par une définition judicieuse des formes d'ondes émises. Dans la mesure où les paramètres des cibles (positions, vitesses, directions d'arrivée (DOA), ...) sont estimés à partir des échos des signaux émis, on comprend aisément que les formes d'ondes employées jouent un rôle clé dans les performances du système. Cette thèse porte sur l'estimation de DOA et sur la conception des formes d'ondes pour un radar MIMO. Le cadre d'étude est restreint au cas où les antennes sont colocalisées et les cibles sont immobiles et supposées ponctuelles. La plupart des travaux antérieurs (au commencement de la thèse) portaient sur le radar MIMO bande étroite et faisaient l'hypothèse d'émetteurs-récepteurs idéaux et indépendants. Cette thèse contribue à élargir le cadre d'étude en s'intéressant d'une part au passage en large bande et d'autre part à la modélisation et à la prise en compte de la non-indépendance des émetteurs-récepteurs et autres imperfections. Dans la mesure où le recours à des signaux large bande est nécessaire lorsqu'une résolution importante est souhaitée, nous nous sommes attachés dans cette thèse à adapter le modèle d'un système de radar MIMO au cas large bande et à proposer de nouvelles techniques visant à améliorer les performances d'estimation de DOA dans le cas de signaux large bande. Cette thèse analyse également l'influence de conditions non idéales comme l'impact des phénomènes de couplage électromagnétique sur les diagrammes de rayonnement dans un réseau d'antennes. Cette étude est menée dans le cas bande étroite. En particulier, nous étudions l'influence du couplage direct entre les réseaux d'antennes d'émission et de réception (appelé « crosstalk ») sur les performances des techniques proposées. Nous établissons un modèle du signal permettant de prendre en compte ce phénomène et proposons une technique de réduction du « crosstalk » qui permet une estimation efficace des DOA des cibles. Nous montrons par ailleurs comment améliorer les performances d'estimation de DOA en présence de diagrammes de rayonnement incluant le couplage entre antennes. Le dernier apport principal de cette thèse est la conception et réalisation d'une plateforme expérimentale comportant une seule architecture d'émetteur-récepteur, qui permet de simuler un système MIMO utilisant des antennes colocalisées en appliquant le principe de superposition. Cette plateforme nous a permis d'évaluer les performances des techniques proposées dans des conditions plus réalistes / A Multiple-Input Multiple-Output (MIMO) radar is a system employing multiple transmitters and receivers in which the waveforms to be transmitted can be totally independent. Compared to standard phased-array radar systems, MIMO radars offer more degrees of freedom which leads to improved angular resolution and parameter identifiability, and provides more flexibility for transmit beampattern design. The main issues of interest in the context of MIMO radar are the estimation of several target parameters (which include range, Doppler, and Direction-of-Arrival (DOA), among others). Since the information on the targets is obtained from the echoes of the transmitted signals, it is straightforward that the design of the waveforms plays an important role in the system accuracy. This document addresses the investigation of DOA estimation of non-moving targets and waveform design techniques for MIMO radar with colocated antennas. Although narrowband MIMO radars have been deeply studied in the literature, the existing DOA estimation techniques have been usually proposed and analyzed from a theoretical point of view, often assuming ideal conditions. This thesis analyzes existing signal processing algorithms and proposes new ones in order to improve the DOA estimation performance in the case of narrowband and wideband signals. The proposed techniques are studied under ideal and non-ideal conditions considering punctual targets. Additionally, we study the influence of mutual coupling on the performance of the proposed techniques and we establish a more realistic signal model which takes this phenomenon into account. We then show how to improve the DOA estimation performance in the presence of distorted radiation patterns and we propose a crosstalk reduction technique, which makes possible an efficient estimation of the target DOAs. Finally, we present an experimental platform for MIMO radar with colocated antennas which has been developed in order to evaluate the performance of the proposed techniques under more realistic conditions. The proposed platform, which employs only one transmitter and one receiver architectures, relies on the superposition principle to simulate a real MIMO system

The diploma thesis focuses on the issue of the system of collection and evaluation of operational events at the DOA organization. It specifies the basic legislative requirements and regulations in the field of reporting incidents of an aircraft technical. For the analysis of the given topic, Czech companies were contacted, which could share their own experience in the framework of security management using a proactive method. Based on the summary of findings, the system of event collection and processing was designed. The system could be used by organizations dealing with the design of aircraft category ELA2

Решена задача локализации источника звука методами машинного обучения. / The problem of localizing a sound source using machine learning methods has been solved.

[pt] Esta tese desenvolve técnicas avançadas de processamento de sinais com arranjos de sensores, tanto para arranjos completamente calibrados quanto parcialmente calibrados. São propostas novas geometrias de arranjos esparsos baseadas em subarranjos lineares esparsos, bem como são desenvolvidos novos algoritmos de estimativa de direção de chegada (DOA) para sinais eletromagnéticos de banda estreita, utilizando-se a teoria de processamento estatístico. Os algoritmos propostos, denominados Generalized Coarray MUSIC (GCA-MUSIC) e Generalized Coarray Root MUSIC (GCA-rMUSIC), expandem a técnica clássica denominada Multiple Signal Classification (MUSIC) para configurações de subarranjos esparsos. Técnicas de projeto de subarranjos lineares esparsos foram propostas, assim como uma análise dos graus de liberdade dos subarranjos (sDoF) em função dos graus de liberdade do arranjo completo (DoF). Além disso, desenvolvem-se versões com tamanho de Janela Variável (VWS) desses algoritmos, que incorporam técnicas de suavização espacial com abertura variável. Esses métodos proporcionam estimativas de direção de alta precisão e conseguem estimar um número maior de fontes do que o número de sensores físicos em cada subarranjo, explorando estruturas de coarranjo específicas. A análise de desempenho demonstra que o GCA-MUSIC e o GCA-rMUSIC, juntamente com suas variantes VWS, melhoram a precisão no contexto de arranjos parcialmente calibrados, onde podem existir incertezas de calibração. Além disso, são apresentadas variantes VWS do algoritmo Coarray MUSIC (CA-MUSIC) para arranjos totalmente calibrados (coerentes), permitindo estratégias de suavização adaptáveis para um desempenho aprimorado. Além do desenvolvimento algorítmico, foram derivadas as Matrizes de Informação de Fisher (FIMs) para o conjunto completo de parâmetros deste modelo de dados generalizado, incluindo tanto as relações de parâmetros consigo próprios quanto cruzados. Essas matrizes levam em consideração as direções das fontes, potências das fontes, potência do ruído e as componentes reais e imaginárias de todos os parâmetros de calibração, representando cenários com fontes correlacionadas e descorrelacionadas. Este trabalho avança significativamente a compreensão teórica dos limites de desempenho da estimativa de direções, fornecendo uma quantificação mais rigorosa dos limitantes de Cramér-Rao. Esses limitantes são particularmente relevantes em cenários com arranjos parcialmente calibrados e fontes descorrelacionadas, conforme demonstrado utilizando-se modelos de dados baseados no produto de Khatri-Rao. / [en] This thesis explores advanced array signal processing techniques for both fully and partially calibrated arrays. We introduce novel sparse array geometries based on sparse linear subarrays and develop new direction-of-arrival (DOA) estimation algorithms for narrowband electromagnetic signals, framed within statistical signal processing principles. The proposed algorithms, named Generalized Coarray MUSIC (GCA-MUSIC) and Generalized Coarray Root MUSIC (GCA-rMUSIC), extend the classical Multiple Signal Classification (MUSIC) framework to sparse subarrays configurations. Sparse linear subarray design techniques were proposed, as well as an analysis of the degrees of freedom of subarrays (sDoF) as a function of degrees of freedom of the whole array (DoF). Additionally, we develop Variable Window Size (VWS) versions of these algorithms, which incorporate flexible spatial smoothing apertures. These methods provide high-accuracy DoA estimates and offer the key advantage of resolving more sources than the number of physical sensors in each subarray by exploiting coarray structures. Performance analysis demonstrates that GCA-MUSIC and GCA-rMUSIC, along with its VWS variants, improve accuracy in the context of partially-calibrated arrays, where calibration uncertainties may exist. Furthermore, VWS variants of the Coarray MUSIC (CA-MUSIC) algorithm are presented for fully calibrated (coherent) arrays, enabling adaptable smoothing strategies for enhanced performance. In addition to algorithmic development, we compute the Fisher Information Matrices (FIMs) for the complete set of parameters in this generalized data model, including both self and cross-coupled parameter relationships. These matrices account for source directions, source powers, noise power, and the real and imaginary components of all calibration parameters, representing both correlated and uncorrelated source scenarios. This work significantly advances the theoretical understanding of DoA estimation performance limits by providing a more rigorous quantification of the Cramér-Rao bounds. These bounds are particularly relevant in scenarios with partially calibrated arrays and uncorrelated sources, as demonstrated using the Khatri-Rao product-based data model.

A direction of arrival (DoA) estimation technique for broadband microwave signals is proposed using a single ultrawideband antenna. It is inspired by the sound source localization ability of a human auditory system using just one ear (monaural localization). By exploiting the incident angle-dependent frequency response of a wideband antenna, the DoA of a broadband microwave signal can be estimated. The DoA estimation accuracies are evaluated for two antenna configurations and microwave signals with different signal-to-noise ratios. Encouraging the DoA estimation performance of the proposed technique is demonstrated in both simulation and experiment.