National security needs dictate the development of new radar systems capable of identifying and tracking exoatmospheric threats to aid our defense. These new radar systems feature reduced noise floors, electronic beam steering, and ultra-wide bandwidths, all of which facilitate threat discrimination. However, in order to identify missile attributes such as RF reflectivity, distance, and velocity, many existing processing algorithms rely upon narrow bandwidth assumptions that break down with increased signal bandwidth. We present a fresh investigation into these algorithms for removing bandwidth limitations and propose novel state-space and direct-data factoring formulations such as * the multidimensional extension to the Eigensystem Realization Algorithm, * employing state-space models in place of interpolation to obtain a form which admits a separation and isolation of solution components, * and side-stepping the joint diagonalization of state transition matrices, which commonly plagues methods like multidimensional ESPRIT. We then benchmark our approaches and relate the outcomes to the Cramer-Rao bound for the case of one and two adjacent reflectors to validate their conceptual design and identify those techniques that compare favorably to or improve upon existing practices.

In this thesis a new approach is proposed for non-uniform linear arrays (NLA) which employs conventional subspace methods to improve the direction of arrival (DOA) estimation performance. Uniform linear arrays (ULA) are composed of evenly spaced sensor elements located on a straight line. ULA&#039 / s covariance matrix have a Vandermonde matrix structure, which is required by fast subspace DOA estimation algorithms. NLA differ from ULA only by some missing sensor elements. These missing elements cause some gaps in covariance matrix and Vandermonde structure is lost. Therefore fast subspace DOA algorithms can not be applied in this case. Linear programming methods and array interpolation methods can be used to solve this problem. However linear programming is computationally expensive and array interpolation is angular sector dependent and requires the same number of sensor in the virtual array. In this thesis, a covariance matrix augmentation method is developed by using the array interpolation technique and initial DOA estimates. An initial DOA estimate is obtained by Toeplitz completion of the covariance matrix. This initial DOA estimates eliminates the sector dependency and reduces the least square mapping error of array interpolation. A Wiener formulation is developed which allows more sensors in the virtual array than the real array. In addition, it leads to better estimates at low SNR. The new covariance matrix is used in the root-MUSIC algorithm to obtain a better DOA estimate. Several computer simulations are done and it is shown that the proposed approach improves the DOA estimation accuracy significantly compared to the same number of sensor ULA. This approach also increases the number of sources that can be identifed.

In this thesis, a Neural Network (NN) based beamforming algorithm is proposed for real time target tracking problem. The algorithm is performed for two applications, linear and cylindrical arrays. The linear array application is implemented with equispaced omnidirectional sources. The influence of the number of antenna elements and the angular seperation between the incoming signals on the performance of the beamformer in the linear array beamformer is studied, and it is observed that the algorithm improves its performance by increasing both two parameters in linear array beamformer. The cylindrical array application is implemented with twelve microstrip patch antenna (MPA) elements. The angular range of interest is divided into twelve sectors. Since three MPA elements are used to form the beam in each sector, the input size of the neural network (NN) is reduced in cylindrical array. According to the reduced size of NN, the training time of the beamformer is decreased. The reduced size of the NN has no degradation in forming the beams to the desired directions. The angular separation between the targets is an important parameter in cylindrical array beamformer.

An antenna array is an indispensable portion of a direction-of-arrival (DOA) estimation operation. A number of error sources in the arrays degrade the DOA estimation accuracy. Mutual coupling effect is one of the main error sources and should be corrected for any antenna array. In this thesis, a system theoretic approach is presented for mutual coupling characterization of antenna arrays. In this approach, the idea is to model the mutual coupling effect through a simple linear transformation between the measured and the ideal array data. In this context, a measurement reduction method (MRM) is proposed to decrease the number of calibration measurements. This new method dramatically reduces the number of calibration measurements for omnidirectional antennas. It is shown that a single calibration measurement is sufficient for uniform circular arrays when MRM is used. The method is extended for the arrays composed of non-omnidirectional (NOD) antennas. It is shown that a single calibration matrix can not properly model the mutual coupling effect in an NOD antenna array. Therefore, a sectorized calibration approach is proposed for NOD antenna arrays where the mutual coupling calibration is done in angular sectors. Furthermore, mutual coupling problem is also investigated for antenna arrays over a perfect electric conductor plate. In this case, reflections from the plate lead to gain/phase mismatches in the antenna elements. In this context, a composite matrix approach is proposed where mutual coupling and gain/phase mismatch are jointly modelled by using a single composite calibration matrix. The proposed methods are evaluated over DOA estimation accuracies using Multiple Signal Classification (MUSIC) algorithm. The calibration measurements are obtained using the numerical electromagnetic simulation tool FEKO. The evaluation results show that the proposed methods effectively realize the mutual coupling calibration of antenna arrays.

L’estimation et la localisation de sources sont des problèmes centraux en traitement d’antenne, en particulier en télécommunication, sismologie, acoustique, ingénierie médicale ou astronomie. Une antenne de capteurs est un système d’acquisition composé par de multiples capteurs qui reçoivent des ondes en provenance de sources de directions différentes: elle échantillonne les champs incidents en espace et en temps.Pour cette raison, des techniques haute résolution comme MUSIC utilisent ces deux éléments de diversité, l’espace et le temps, afin d’estimer l’espace signal engendré par les sources incidentes, ainsi que leur direction d’arrivée. Ceci est généralement atteint par une estimation préalable de statistiques de deuxième ordre ou d’ordre supérieur, comme la covariance spatiale de l’antenne, qui nécessitent donc de temps d’observation suffisamment longs.Seulement récemment, l’analyse tensorielle a été appliquée au traitement d’antenne, grâce à l’introduction, comme troisième modalité (ou diversité), de la translation en espace d’une sous-antenne de référence, sans faire appel à l’estimation préalable de quantités statistiques.Les décompositions tensorielles consistent en l’analyse de cubes de données multidimensionnelles, au travers de leur décomposition en somme d’éléments constitutifs plus simples, grâce à la multilinéarité et à la structure de rang faible du modèle sous-jacent.Ainsi, les mêmes techniques tensorielles nous fournissent une estimée des signaux eux-mêmes, ainsi que de leur direction d’arrivée, de façon déterministe. Ceci peut se faire en vertu du modèle séparable et de rang faible vérifié par des sources en bande étroite et en champs lointain.Cette thèse étudie l’estimation et la localisation de sources par des méthodes tensorielles de traitement d’antenne.Le premier chapitre présente le modèle physique de source en bande étroite et en champs lointain, ainsi que les définitions et hypothèses fondamentales. Le deuxième chapitre passe en revue l’état de l’art sur l’estimation des directions d’arrivée, en mettant l’accent sur les méthodes haute résolution à sous-espace. Le troisième chapitre introduit la notation tensorielle, à savoir la définition des tableaux de coordonnées multidimensionnels, les opérations et décompositions principales. Le quatrième chapitre présente le sujet du traitement tensoriel d’antenne au moyen de l’invariance par translation.Le cinquième chapitre introduit un modèle tensoriel général pour traiter de multiples diversités à la fois, comme l’espace, le temps, la translation en espace, les profils de gain spatial et la polarisation des ondes élastiques en bande étroite.Par la suite, les sixième et huitième chapitres établissent un modèle tensoriel pour un traitement d’antenne bande large cohérent. Nous proposons une opération de focalisation cohérente et séparable par une transformée bilinéaire et par un ré-échantillonnage spatial, respectivement, afin d’assurer la multilinéarité des données interpolées.Nous montrons par des simulations numériques que l’estimation proposée des paramètres des signaux s’améliore considérablement, par rapport au traitement tensoriel classique en bande étroite, ainsi qu’à MUSIC cohérent bande large.Egalement, tout au long de la thèse, nous comparons les performances de l’estimation tensorielle avec la borne de Cramér-Rao du modèle multilinéaire associé, que nous développons, dans sa forme la plus générale, dans le septième chapitre. En outre, dans le neuvième chapitre nous illustrons une application à des données sismiques réelles issues d’une campagne de mesure sur un glacier alpin, grâce à la diversité de vitesse de propagation.Enfin, le dixième et dernier chapitre de cette thèse traite le sujet parallèle de la factorisation spectrale multidimensionnelle d’ondes sismiques, et présente une application à l’estimation de la réponse impulsionnelle du soleil pour l’héliosismologie. / Source estimation and localization are a central problem in array signal processing, and in particular in telecommunications, seismology, acoustics, biomedical engineering, and astronomy. Sensor arrays, i.e. acquisition systems composed of multiple sensors that receive source signals from different directions, sample the impinging wavefields in space and time. Hence, high resolution techniques such as MUSIC make use of these two elements of diversities: space and time, in order to estimate the signal subspace generated by impinging sources, as well as their directions of arrival. This is generally done through the estimation of second or higher orders statistics, such as the array spatial covariance matrix, thus requiring sufficiently large data samples. Only recently, tensor analysis has been applied to array processing using as a third mode (or diversity), the space shift translation of a reference subarray, with no need for the estimation of statistical quantities. Tensor decompositions consist in the analysis of multidimensional data cubes of at least three dimensions through their decomposition into a sum of simpler constituents, thanks to the multilinearity and low rank structure of the underlying model. Thus, tensor methods provide us with an estimate of source signatures, together with directions of arrival, in a deterministic way. This can be achieved by virtue of the separable and low rank model followed by narrowband sources in the far field. This thesis deals with source estimation and localization of multiple sources via these tensor methods for array processing. Chapter 1 presents the physical model of narrowband elastic sources in the far field, as well as the main definitions and assumptions. Chapter 2 reviews the state of the art on direction of arrival estimation, with a particular emphasis on high resolution signal subspace methods. Chapter 3 introduces the tensor formalism, namely the definition of multi-way arrays of coordinates, the main operations and multilinear decompositions. Chapter 4 presents the subject of tensor array processing via rotational invariance. Chapter 5 introduces a general tensor model to deal with multiple physical diversities, such as space, time, space shift, polarization, and gain patterns of narrowband elastic waves. Subsequently, Chapter 6 and Chapter 8 establish a tensor model for wideband coherent array processing. We propose a separable coherent focusing operation through bilinear transform and through a spatial resampling, respectively, in order to ensure the multilinearity of the interpolated data. We show via computer simulations that the proposed estimation of signal parameters considerably improves, compared to existing narrowband tensor processing and wideband MUSIC. Throughout the chapters we also compare the performance of tensor estimation to the Cramér-Rao bounds of the multilinear model, which we derive in its general formulation in Chapter 7. Moreover, in Chapter 9 we propose a tensor model via the diversity of propagation speed for seismic waves and illustrate an application to real seismic data from an Alpine glacier. Finally, the last part of this thesis in Chapter 10 moves to the parallel subject of multidimensional spectral factorization of seismic ways, and illustrates an application to the estimation of the impulse response of the Sun for helioseismology.

Made available in DSpace on 2014-12-17T14:56:03Z (GMT). No. of bitstreams: 1 OsmarADJ.pdf: 1159660 bytes, checksum: 65307a903dfe1a1f71297194d1c7e2a5 (MD5) Previous issue date: 2004-12-22 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / This dissertation presents a new proposal for the Direction of Arrival (DOA) detection problem for more than one signal inciding simultaneously on an antennas array with linear or planar geometry by using intelligent algorithms. The DOA estimator is developed by using techniques of Conventional Beam-forming (CBF), Blind Source Separation (BSS), and the neural estimator MRBF (Modular Structure of Radial Basis Functions). The developed MRBF estimator has its capacity extended due to the interaction with the BSS technique. The BSS makes an estimation of the steering vectors of the multiple plane waves that reach the array in the same frequency, that means, obtains to separate mixed signals without information a priori. The technique developed in this work makes possible to identify the multiple sources directions and to identify and to exclude interference sources / Esta disserta??o apresenta uma nova proposta para os problemas de detec??o de dire??o de chegada para mais de um sinal incidindo simultaneamente sobre um arranjo de antenas de geometria planar ou linear empregando algoritmos inteligentes. O estimador de DOA ? desenvolvido utilizando as t?cnicas de Conforma??o de Feixes Digital Convencional (CBF - Conventional Beamforming), de Separa??o Cega de Fontes (BSS {Blind Source Separation) e o estimador neural MRBF (Modular Structure of Radial Basis Functions). O estimador MRBF desenvolvido tem sua capacidade ampliada gra?as ?a intera??o com a t?cnica BSS, a qual faz uma estima??o dos vetores de guiamento das m?ltiplas ondas planas que alcan?am o arranjo na mesma freq??ncia, isto ?, consegue separar sinais misturados sem informa??es a priori. A t?cnica desenvolvida neste trabalho possibilita identificar a dire??o de m?ltiplas fontes e identificar e excluir as fontes de interfer?ncia

Orientador: Amauri Lopes / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-09T06:28:20Z (GMT). No. of bitstreams: 1 Krummenauer_Rafael_M.pdf: 1711180 bytes, checksum: e9aa73aac9d705c24c2bec02b202f76e (MD5) Previous issue date: 2007 / Resumo: Esta dissertação trata do problema de estimação de direção de chegada (DOA) de ondas planas usando um arranjo linear uniforme de sensores. Estamos interessados em situações nas quais a relação sinal-ruido 'e baixa e o espaçamento angular entre as fontes de sinal 'e pequeno. Baseamos nossa proposta nos m'etodos MODE, MODEX e MODEX Modificado, que sao metodos eficientes existentes na literatura. Inspirados em conceitos de filtragem linear e no criterio da maxima verossimilhança, propomos um procedimento que ameniza o efeito do ruido no resultado da estimação. Este procedimento consiste em filtrar os dados recebidos e modificar adequadamente a função de verossimilhan¸ca utilizada no processo de obtenção das estimativas. Simulações numericas mostram que o desempenho do metodo proposto 'e melhor que aqueles correspondentes aos m'etodos MODE, MODEX e MODEX Modificado, alcançando menores valores de erro quadratico medio e de polarização / Abstract: This work deals with the problem of estimating the direction of arrival (DOA) of plane waves using a uniform linear array of sensors. We are concerned with situations where the signal-to-noise ratio is low and the signal sources are spatially close. Our proposal is based on MODE, MODEX and Modified MODEX, that are efficient methods proposed in the literature. Inspired in concepts of linear filtering and in the maximum likelihood criterion, we propose a procedure that reduces the effect of noise in the estimation result. This procedure consists on filtering the received data and on modifying the likelihood function used to obtain the estimates. Numerical simulations show that the performance of the proposed method is better than those of MODE, MODEX and Modified MODEX methods, achieving lower mean square error and lower bias / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

Orientador: Amauri Lopes / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-09T08:58:42Z (GMT). No. of bitstreams: 1 Silva_FrancisleiJoseda_M.pdf: 1914501 bytes, checksum: f819de68e8cb02f4b9bc4a46d9787202 (MD5) Previous issue date: 2007 / Resumo: Este trabalho aborda o problema de estimação da direção de chegada (DOA) de ondas planas usando arranjo de sensores. Existem diversos estimadores para DOA relatados na literatura. Dentre os estimadores de alta resolução, se destacam os métodos MODE e MODEX, que possuem como base o estimador de máxima verossimilhança (MLE). Este trabalho apresenta o desenvolvimento dos métodos MODE, MODEX e de uma versão melhorada do MODEX, o método MODEX Modi?ed. Estes dois últimos estimadores produzem várias estimativas candidatas e usam o critério de máxima verossimilhança para selecionar aquelas que representam as melhores estimativas para os ângulos de chegada. Entretanto, para uma relação sinalruído baixa, estes métodos sofrem uma forte degradação na escolha das candidatas. Na busca de reduzir esta degradação, é apresentada uma proposta de ?ltragem nos sinais captados pelos sensores, com o objetivo de melhorar a relação sinalruído. São propostos dois projetos de ?ltro FIR: um por alocação de pólos e zeros, e outro por amostragem em freqüência. Os resultados obtidos mostram que esta proposta de ?ltragem é válida e que se consegue reduzir signi?cativamente a SNR do limiar de desempenho apresentado pelos métodos MODEX e MODEX Modi?ed. / Abstract: This work deals with the estimation of the direction of arrival (DOA) of plane waves using array of sensors. There are various estimators for DOA reported in literature. The MODE and MODEX methods, based on the maximum likelihood criterion, are the best high resolution DOA estimators. This work presents the development of these methods as well as of an improved version of the MODEX, named MODEX Modi?ed. MODEX and MODEX Modi?ed produce some estimates that are candidates for the DOA estimation and use the maximum likelihood criterion to select the best ones. However, for low signaltonoise ratio, the selection process suffers a strong performance degradation. In order to reduce this degradation, this work proposes to ?lter the received signals aiming to improve the signaltonoise ratio. Two FIR ?lters are considered: one composed by poles and zeros and another obtained by sampling in the frequency domain. Simulation results show that this proposal improves signi?cantly the performance of both MODEX and MODEX Modi?ed. / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

La densification des réseaux allant de pair avec le déploiement de petites cellules, les systèmes Massive MIMO disposent de caractéristiques prometteuses pour accroître la capacité des réseaux au travers des techniques de formation de faisceau, appelées beamforming. Les transmissions aux longueurs d’onde millimétriques (mmWave) sont, quant à elle, très convoitées car, non seulement les bandes passantes exploitables sont extrêmement larges, mais le canal de propagation est principalement Line-of-Sight (LOS), ce qui correspond à la visibilité directe entre le terminal et la station de base. L’attrait que peut avoir un système multi-utilisateurs Massive MIMO à de telles fréquences provient, en partie, du faible encombrement du réseau d’antennes, mais aussi du fort gain de beamforming dont il permet de bénéficier afin de contrecarrer les fortes pertes en espace libre que subissent les signaux à de telles longueurs d’onde. Dans un premier temps nous montrons comment l’augmentation de la fréquence porteuse impacte les performances de deux précodeurs connus. Au travers d’une modélisation déterministe et géométrique du canal, on simule un scénario Outdoor à faible mobilité et à forte densité de population en mettant en avant l’influence du trajet direct et des trajets réfléchis sur les performances. Plus précisément on prouve qu’en configuration purement LOS, le précodeur Zero-Forcing est beaucoup plus sensible à la structure du réseau d’antennes, et à la position des utilisateurs, que le Conjugate Beamforming (aussi connu sous le nom de retournement temporel). On introduit alors un précodeur basé uniquement sur la position angulaire des utilisateurs dans la cellule en référence à la station de base, puis l’on compare ses performances à celles des deux autres. La robustesse d’une telle implémentation à une erreur d’estimation d’angles est illustrée pour un scénario spécifique afin de souligner la pertinence des solutions angulaires, une direction étant plus facile à estimer et son évolution dans le temps plus prévisible.On décrit dans un second temps comment la connaissance des positions angulaires des utilisateurs permet d’accroître la capacité de la cellule par le biais d’un procédé d’allocation de puissance reposant sur une évaluation de l’interférence que chaque faisceau génère sur les autres. On prouve à l’aide de simulations que l’obtention de cette interférence, même exprimée sous une forme très simplifiée, permet d’améliorer très nettement la capacité totale de la cellule. Enfin, nous introduisons les systèmes Hybrides Numériques et Analogiques ayant récemment été proposés afin de permettre à une station de base de conserver un large nombre d’antennes, nécessaire à l’obtention d’un fort gain de beamforming, tout en réduisant le nombre de chaînes Radiofréquences (RF). On commence par décrire une solution permettant à un terminal de former un faisceau dont la direction s’adapte à sa propre inclinaison, en temps réel, pour toujours viser la station de base. On compare ensuite les performances de tels récepteurs, associés à des stations de base Massive MIMO, avec celles d’une solution hybride connue, le nombre de chaînes RF des deux systèmes étant identiques. Principalement, la flexibilité et la capacité d’évolution de ces systèmes est mise en avant, ces deux atouts étant particulièrement pertinents pour de nombreux environnements à forte densité de population. / As wireless communication networks are driven toward densification with small cell deployments, massive MIMO technology shows great promises to boost capacity through beamforming techniques. It is also well known that millimeter-Wave systems are going to be an important part of future dense network solutions because, not only do they offer high bandwidth, but channel is mostly Line-of-Sight (LOS). The attractiveness of using a multi-user Massive MIMO system at these frequencies comes partly from the reduced size of a many antenna base station, but also from the high beamforming gains they provide, which is highly suited to combat the high path losses experienced at such small wavelengths. First we show how raising the carrier frequency impacts the performance of some linear precoders widely used in Massive MIMO systems. By means of a geometrical deterministic channel model, we simulate a dense outdoor scenario and highlight the influence of the direct and multi-paths components. More importantly we prove that, in a Line-of-Sight (LOS) configuration, the discriminating skill of the well-known Zero Forcing precoder is much more sensitive to the antenna array structure and the user location than the Conjugate Beamforming precoder, also known as Time-Reversal. A precoder based on the knowledge of the angular position of all users is then introduced and compared to the other precoders based on channel response knowledge. Its robustness against angle estimation error is illustrated for a specific scenario and serves to back up the importance such a solution represents for future dense 5G networks, angular information being easier to estimate, and more so to keep track of.After that, we show how the knowledge of Directions of Arrival can be used to increase the sum capacity of a multi-user transmission through leakage based power allocation. This allocation uses an estimation of inter-user interference, referred to as Leakage, and we show through simulations how this factor, even under its most simplified form, improves realistic transmissions. Moreover this solution is not iterative and is extremely easy to implement which makes it particularly well suited for high deployment scenarios.Finally we introduce the Hybrid Analog and Digital Beamforming systems that have recently emerged to retain a high number of antennas without as many Radio Frequency (RF) chains, in order to keep high beamforming gains while lowering the complexity of conceiving many antenna base stations. We first describe a user equipment solution allowing the system to form a beam that adapts to its own movement so that it always focuses its energy toward the base station, using an on-board analog array and an Inertial Measurement Unit. Then we compare the performance of a known Hybrid solution with a fully digital Massive MIMO system, having as many RF chains as the Hybrid system, but serving user equipments with beamforming abilities. Mostly we emphasize how such a system allows for great flexibility and evolution, both traits being invaluable features in many future networks.

[pt] Em sistemas de comunicações móveis, a modulação digital em fase (PSK)é amplamente utilizada em esquemas de transmissão em rádio-propagação. Trabalhos anteriores consideraram alguns métodos baseados no critério de máxima verossimilhança (MV) para estimação de direção-de-chegada de sinais genéricos que atingem um conjunto (array) de sensores. Esta tese propõe um novo estimador MV para a direção-de-chegada, desenvolvido especificamente para sistemas de comunicação PSK. Dois modelos de transmissão são concebidos para estimação dos parâmetros: um mais idealizado, considerando todas as portadoras alinhadas no tempo com o receptor, e outro que considera este desalinhamento na forma de retardo. O número de parâmetros a serem conjuntamente estimados é significativamente reduzido ao se calcular o valor esperado dos sinais medidos no array de antenas com relação µas fases de modulação (dados de informação). O desempenho do estimador em vários cenários simulados é apresentado e comparado ao desempenho do estimador MV clássico desenvolvido sem considerar uma estrutura específica para o sinal. Limitantes de Cramér-Rao para os cenários de portadora única também são calculados. O método proposto se mostra mais robusto por apresentar melhor desempenho que o estimador MV clássico em todas as simulações. / [en] In mobile communication systems, phase shift keying (PSK) modulation is widely used in digital transmission schemes. Previous works have considered several maximum likelihood (ML) methods for the direction-of-arrival (DOA) estimation of generic signals reaching a phased-array of sensors. This thesis proposes a new ML DOA estimator designed to be used in PSK communication systems. Two transmission models are considered for parameter estimation: a simpler one, considering all carrier clocks time-aligned with the receiver clock, and another that considers this misalignment as a delay for each carrier. The number of parameters to be jointly estimated is significantly reduced when the expected value of the antenna array measured signals with respect to the modulation phases is evaluated. The estimator performance in several simulation scenarios is presented and compared to the performance of a classic ML estimator designed for all sorts of signal models. Cramér-Rao bounds for single carrier scenarios are also evaluated. The proposed method robustly outperforms the classic ML estimator in all simulations.