The angle of arrival estimation of multiple sources plays a vital role in the field of array signal processing as MIMO systems can be employed at both the transmitter and the receiver end and the system capacity, reliability and throughput can be significantly increased by using array signal processing. Almost all applications require accurate direction of arrival (DOA) estimation to localize the sources of the signals. Another important parameter of localization systems is the array geometry and sensor design which can be application specific and is used to estimate the DOA. In this work, various array geometries and arrival estimation algorithms are studied and then a new scheme for multiple source estimation is proposed and evaluated based on the performance of subspace and non-subspace decomposition methods. The proposed scheme has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation and Bartlett estimation techniques. The new scheme has a better performance advantage at low and high signal to noise ratio values (SNRs). The research work also studies different array geometries for both single and multiple incident sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna array elements. This research also considers the shape of the ground plane and its effects on the angle of arrival estimation and in addition it shows how the mutual couplings between the elements effect the overall estimation and how this error can be minimised by using a decoupling matrix. At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver base station is designed and tested. The antenna radiation patterns in the azimuth angle are almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral with striplines feeding network and biased components to improve the impedance bandwidth. The antenna provides the benefit of small size, and re-configurability and is very well suited for the asset tracking applications.

Sensor network performance is governed by the physical placement of sensors and their geometric relationship to the events they measure. To illustrate this, the entirety of this thesis covers the following interconnected subjects: 1) graphical analysis of the variance of the estimation error caused by physical characteristics of an acoustic target source and its geometric location relative to sensor arrays, 2) event/anomaly detection method for time aggregated point sensor data using a parametric Poisson distribution data model, 3) a sensor reduction or placement technique using Bellman optimal estimates of target agent dynamics and probabilistic training data (Goode, Chin, & Roan, 2011), and 4) transforming event monitoring point sensor data into event detection and classification of the direction of travel using a contextual, joint probability, causal relationship, sliding window, and geospatial intelligence (GEOINT) method. / Master of Science

In modern combat aircraft, the most common localization method integrates a Global Navigation Satellite System (GNSS) with an Inertial Navigation System (INS). Although GNSS is the optimal choice for navigation, there are situations when the GNSS satellite signal is unavailable. This can happen due to various reasons such as jamming, physical obstacles, or technical failures. An alternative method to GNSS is utilizing Signals of Opportunity (SOP), which leverages signals not intended for navigation, such as those from cellular towers. These signals are transmitted from non-controllable sources, and challenges may arise due to the lack of guarantee regarding their quality and availability. Therefore, it is crucial that any estimation method utilizing SOP is robust to ensure accurate aircraft localization. This thesis investigates three different localization approaches to address this challenge. This study explores SOP sources with both known and unknown positions. For known signal source positions, an Extended Kalman Filter (EKF) based solution is utilized as a baseline to evaluate how well unknown signal sources can be used to estimate the aircraft's location. To address the challenge of unknown signal source positions, an EKF combined with a Simultaneous Localization and Mapping (SLAM) method, referred to as EKF SLAM, is used. In this case, the sources are introduced through two different approaches. The first approach, undelayed initialization, introduces the signal source directly when observed. The second approach, delayed initialization, involves inverse depth parameterization (IDP) and preprocessing of the signal source position before fully introducing it into the aircraft system. While both approaches outperform an unassisted INS approach, they do not achieve the same level of performance as when the source positions are known. Moreover, various factors, including the aircraft's trajectory, measurement noise, measurement frequency, and the initial covariance of new landmarks, influence the performance of the EKF SLAM approaches. Additionally, delayed initialization is strongly influenced by a threshold assessing landmark position estimate linearity, underscoring its sensitivity to accuracy. The concept behind delayed initialization aims to reduce the error of the signal source position before it is introduced to the system. This method has been proven to significantly reduce the signal source position error. However, its robustness is influenced by several factors, including the parallax angle, sudden changes in the aircraft's direction, and particularly the initial covariance of a landmark estimate. The accuracy of the aircraft's position is crucial, resulting in a trade-off between preprocessing and rapidly initializing a signal source position to the aircraft system. In contrast, undelayed initialization is less sensitive to trajectory changes, even though it introduces the signal sources with greater initial error. There is a significant difference in computational time when comparing known and unknown sources. As the number of sources increases, the computational time for unknown sources is more affected than for known sources. The delayed source initialization method increases computational time due to its preprocessing, especially as more sources are used. Conversely, initializing sources directly reduces the computational time, as no preprocessing is required. / I moderna stridsflygplan är den vanligaste lokaliseringsmetoden att integrera ett Global Navigation Satellite System (GNSS) med ett Inertial Navigation System (INS). Även om GNSS är det optimala valet för navigation finns det situationer när GNSS-satellitsignalen inte är tillgänglig. Detta kan inträffa på grund av olika orsaker som störningar, fysiska hinder eller tekniska fel. En alternativ metod till GNSS är att använda Signals of Opportunity (SOP), som utnyttjar signaler som inte är avsedda för navigation, till exempel de från mobilmaster. Dessa signaler kommer från okontrollerbara källor, vilket kan medföra utmaningar på grund av att deras kvalitet och tillgänglighet inte kan garanteras. Därför är det viktigt att varje lokaliseringsmetod som använder SOP är robust för att säkerställa en bra och korrekt flygplans positionering. Detta examensarbete undersöker tre olika lokaliseringsmetoder för att hantera denna utmaning. Denna studie utforskar SOP-källor med både kända och okända positioner. För kända positioner används en lösning baserad på ett Extended Kalman Filter (EKF) som en baslinje för att utvärdera hur väl okända signalkällor kan användas för att uppskatta flygplanets position. För att hantera utmaningen med okända signalkällors positioner används ett EKF kombinerad med en metod vid namn Simultaneous Localization and Mapping (SLAM), även kallad EKF SLAM. I detta fall introduceras källorna genom två olika tillvägagångssätt. Det första tillvägagångssättet, ofördröjd initialisering, introducerar signalkällan direkt när den observeras. Det andra tillvägagångssättet, fördröjd initialisering, involverar inverse depth parameterization (IDP) och förbearbetning av signalkällans position innan den introduceras i flygplanets lokaliseringssystem. Även om båda tillvägagångssätten presterar bättre än en oassisterad INS-metod uppnår de inte samma prestandanivå som när källornas position är kända. Dessutom påverkar olika faktorer prestandan hos EKF SLAM-metoderna, vilka främst är flygplanets flygbana, mätbrus, mätfrekvens och den initiala kovariansen av nya landmärken. Dessutom påverkas fördröjd initialisering starkt av en tröskel som bedömer linjäritet hos landmärkes positionen, vilket understryker dess känslighet för noggrannhet. Konceptet bakom fördröjd initialisering syftar till att minska felet i signalkällans position innan den introduceras i lokaliseringssystemet. Denna metod har visat sig kunna minska felet i signalkällans position avsevärt. Emellertid påverkas dess robusthet av flera faktorer, inklusive parallaxvinkeln, plötsliga förändringar i flygplanets riktning och särskilt den initiala kovariansen av uppskattningen av ett landmärkes position. Noggrannheten i flygplanets position är avgörande, vilket resulterar i en avvägning mellan förbearbetning och snabb initialisering av en signalkällas position till flygplanets lokaliseringssystem. Till skillnad från fördröjd initialisering är ofördröjd initialisering mindre känslig för förändringar i flygbanan, även om den introducerar signalkällorna med större initialt fel. Det finns en anmärkningsvärd skillnad i beräkningstid när man jämför kända och okända källors. När antalet källor ökar påverkas beräkningstiden för okända källor mer än för kända källor. Den fördröjda källinitialiseringsmetoden ökar beräkningstiden på grund av dess förbearbetning, särskilt när många källor används. Däremot minskar beräkningstiden när källor initialiseras direkt, eftersom ingen förbearbetning krävs.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Este trabalho se propÃe a investigar e propor diferentes tÃcnicas de estimaÃÃo de canal de mÃltiplas entradas e mÃltiplas saÃdas (MIMO) para sistemas de comunicaÃÃo multiusuÃrio operando em regime de interferÃncia em cenÃrio de mÃltiplas cÃlulas. AtenÃÃo particular à dada ao caso onde as estaÃÃes rÃdio-base sÃo equipadas com arranjos de antenas apresentando grande quantidade de antenas, configurando o que se tem referido na literatura como sistemas de comunicaÃÃo MIMO de grande dimensÃo (VL-MIMO, do inglÃs: very large MIMO). Algumas destas tÃcnicas exploram as propriedades das grandes matrizes aleatÃrias e sÃo menos afetadas pela contaminaÃÃo de pilotos. Nesta dissertaÃÃo, os parÃmetros do canal VL-MIMO sÃo estimados a partir de uma decomposiÃÃo em autovalores (EVD, do inglÃs: eigenvalue-decomposition) da matriz de covariÃncia na saÃda do arranjo de antenas receptoras. Esta tÃcnica se mostra menos sensÃvel à presenÃa de interferÃncia do que outras que nÃo exploram propriedades especÃficas da matriz de canal VL-MIMO, como à o caso da soluÃÃo clÃssica dos mÃnimos quadrados (LS, do inglÃs: least-squares). Nesse contexto, propÃe-se ainda uma soluÃÃo para o fator de ambiguidade multiplicativa do mÃtodo baseado em EVD, utilizando um simples produto de Khatri-Rao. Na segunda parte desta dissertaÃÃo, as propriedades dos sistemas VL-MIMO sÃo empregadas num problema de localizaÃÃo de fontes, a fim de determinar a direÃÃo de chegada (DOA) dos sinais incidentes sobre o arranjo, provenientes da cÃlula em questÃo. Explorando o subespaÃo de representaÃÃo dos sinais interferentes, propÃe-se o uso de um algoritmo de classificaÃÃo de tipo MUSIC para estimar a matriz de canal de forma cega. O mÃtodo proposto converte os altos ganhos de resoluÃÃo dos arranjos VL-MIMO em capacidade de reduÃÃo de interferÃncia, podendo fornecer estimativas do canal adequadas, mesmo sob nÃveis fortes de interferÃncia e tambÃm em casos onde os sinais do usuÃrio desejado e dos interferentes sÃo altamente correlacionados espacialmente. Extensas campanhas de simulaÃÃo computacional foram realizadas, dandoum carÃter exploratÃrio a esta dissertaÃÃo no sentido de abranger diferentes cenÃrios e avaliar as tÃcnicas investigadas em comparaÃÃo com soluÃÃes jà consolidadas, permitindo assim a elaboraÃÃo de um panorama mais completo de caracterizaÃÃo dos problemas de estimaÃÃo de parÃmetros no caso VL-MIMO. / The aim of this dissertation is mainly to investigate and propose different channel estimation techniques for a multicell multiuser multiple-input multiple-output (MIMO) communication system. Particular attention is payed to the case that is referred to as very large (VL) MIMO (VL-MIMO) arrays, where the base stations are equipped with a great (or even huge) number of antenna sensors. Some of these techniques exploit properties issued from the (large) Random Matrices Theory and are therefore less affected by the so-called pilot contamination effect. In this work, the parameters of the VL-MIMO channel are estimated from the eigenvalue decomposition (EVD) of the output covariance matrix of the receive antenna array. This technique is more robust to the interference of signals from other cells compared with methods that do not exploit the specific properties of the VL-MIMO channel matrix, which is the case of the classical least squares (LS) solution. In this context, this work also proposes a simpler way to resolve the scaling ambiguity remaining from the EVD-based method using the Khatri-Rao product. The second part of this dissertation exploits the VL-MIMO properties on a source localization problem, aiming to determine the direction of arrival (DoA) of the signals impinging on the antenna array from a given desired cell. Based on the subspace representation of the outer cell interference signals, we propose a new blind MUSIC-like classification algorithm to estimate the channel matrix. The proposed technique convert the high resolution gains of the VL-MIMO arrays into ability to reduce power of undesired signals, yielding good channel estimates even under high interference power levels, and including cases where desired and undesired signals are strongly correlated. Computer simulations have been done in order to cope with different situations and propagation scenarios, thus yielding an exploratory character to our research and allowing us to evaluate and assess the investigated algorithms, comparing them to consolidated solutions in order to establish a complete overview of the parameter estimation problem in the VL-MIMO case.

Non-destructive testing (NDT) techniques are critical to ensure integrity and safety of engineered structures. Structural health monitoring (SHM) is considered as the next step in the field enabling continuous monitoring of structures. The first part of the thesis concerns NDT and SHM using guided waves in plates, or Lamb waves, to perform imaging of plate structures. The imaging is performed using a fixed active array setup covering a larger area of a plate. Current methods are based on conventional beamforming techniques that do not efficiently exploit the available data from the small arrays used for the purpose. In this thesis an adaptive signal processing approach based on the minimum variance distortionless response (MVDR) method is proposed to mitigate issues related to guided waves, such as dispersion and the presence of multiple propagating modes. Other benefits of the method include a significant increase in resolution. Simulation and experimental results show that the method outperforms current standard processing techniques. The second part of the thesis addresses transducer design issues for resonant ultrasound inspections. Resonant ultrasound methods utilize the shape and frequency of the object's natural modes of vibration to detect anomalies. The method considered in the thesis uses transducers that are acoustically coupled to the inspected structures. Changes in the transducer's electrical impedance are used to detect defects. The sensitivity that can be expected from such a setup is shown to highly depend on the transducer resonance frequency, as well as the working frequency of the instrument. Through simulations and a theoretical argumentation, optimal conditions to achieve high sensitivity are given.

Dans l'océan, les changements de température induisent des perturbations de la vitesse de propagation des ondes acoustiques. La tomographie acoustique océanique utilise les fluctuations de signaux acoustiques enregistrés pour cartographier ces perturbations de vitesse du son. Cette étude propose une méthode alternative utilisant la direction de propagation des ondes acoustiques (plutôt que les temps de propagation utilisés classiquement) pour imager un guide d'onde océanique peu profond (~100 m), petite échelle (1 à 10 km), avec une haute résolution spatiale (10 m horizontalement, 2 m en profondeur). Dans ce contexte, les ondes acoustiques basse fréquence (~1 kHz) à large bande spectrale (~1.5 kHz) se propagent selon des trajectoires multiples assimilables à des rayons géométriques épais spatialement. L'utilisation d'un couple d'antennes (émission/réception) et de la double formation de voies permet de séparer les signaux en provenance des différents trajets acoustiques et de mesurer leur : temps de propagation (TP), direction d'arrivée (DA) et direction de départ (DD). Dans l'hypothèse de faibles perturbations, les variations des TP, DA et DD sont reliées linéairement aux perturbations de la distribution de vitesse du son de manière analytique. Cette formulation, basée sur la physique de la diffraction de Born au 1er ordre, utilise des fonctions noyaux appelées : noyaux de sensibilité temps-angles (NSTA). Les méthodes classiques d'inversion permettent alors de retrouver les perturbations de vitesse à partir des variations de TP, DA et DD en utilisant les NSTA. Les méthodes développées ont été validées sur données simulées, puis appliquées à des données réelles d'expériences à échelle réduites réalisées dans la cuve ultrasonore de l'ISTerre, Grenoble. / In the ocean, temperature changes induce sound-speed perturbations. Ocean acoustic tomography uses the fluctuations of recorded acoustic signals, to map those sound-speed perturbations. To this end, sound-speed perturbations are classically related to the acoustic-wave travel-times measured on the records. This study suggests an alternative method to perform acoustic thermometry based on acoustic-wave propagation directions. It allows imaging a shallow-water waveguide (~100 m), at small scale (1 to 10 km), with high spatial resolution (10 m in range, 2 m in depth). In this context, wideband (~1.5 kHz) low frequency (~1 kHz) acoustic waves propagates along multiple paths similar to spatially « fat » geometrical rays. Using a pair of arrays (source/receiver) and the double-beamforming processing to separate acoustic signals coming from different paths and measure their: travel-time (TT), directions-of-arrival (DOA) and directions-of-departure (DOD). Under the hypothesis of small perturbations, TP, DOA and DOD variations are linearly related to sound-speed perturbations in an analytical way. This formulation based on Born's diffraction physics at the first order uses kernel functions called: the time-angle sensitivity kernels (T-A-SK). The T-A-SK model is then combined to classical inversion methods to retrieve sound-speed perturbations from TT, DOA and DOD variations. The methods developed here have been validated on simulated data, and applied on real small-scale data coming from the ultrasonic tank of the ISTerre, Grenoble.

[pt] A estimação de direção de chegada (DoA) é uma importante área de processamento de arranjos de sensores que é encontrada em uma ampla gama de aplicações de engenharia. Este fato, juntamente com o desenvolvimento da área de Compressed Sensing (CS) nos últimos anos, são a principal motivação desta dissertação. Nesta dissertação, é apresentada uma formulação do problema de estimação de direção de chegada como um problema de representação esparsa da sinal e vários algoritmos de recuperação esparsa são derivados e investigados para resolver o problema atual. Os algoritmos propostos são baseados na incorporação da informação prévia sobre o sinal esparso no processo de estimativa. Na primeira parte, nos concentramos no desenvolvimento de dois algoritmos Bayesianos , que se baseiam principalmente no algoritmo iterative hard thresholding (IHT). Devido ao desempenho inferior dos algoritmos convencionais de estimação de chegada em cenários com fontes correlacionadas, nós prestamos atenção especial ao desempenho dos algoritmos propostos nesta condição. Na segunda parte, o problema de otimização baseados na minimização da norma l1 é apresentado e um algoritmo bayesiano é proposto para resolver o problema chamado basis pursuit denoising (BPDN). Os resultados da simulação mostram que os estimadores Bayesianos superam os estimadores não Bayesianos e que a incorporação do conhecimento prévio da distribuição do sinal melhorou substancialmente o desempenho dos algoritmos. / [en] Direction of arrival (DoA) estimation is a key area of sensor array processing which is encountered in a broad range of important engineering applications. This fact together with the development of the Compressed Sensing (CS) area in the last years are the principal motivation of this thesis. In this dissertation, a formulation of the source localization problem as a sparse signal representation problem is presented and several sparse recovery algorithms are derived and investigated for solving the current problem. The proposed algorithms are based on the incorporation of the prior information about the sparse signal in the estimation process. In the first part, we focus on the development of two Bayesian greedy algorithms which are principally based on the iterative hard thresholding (IHT) algorithm. Due to the inferior performance of the conventional DoA estimation algorithm in scenarios with correlated sources, we pay special attention to the performance of the proposed algorithms under this condition. In the second part, the optimization problem using a l1 penalty is introduced and a Bayesian algorithm for solving the basis pursuit denoising problem is presented. Simulation results shows that Bayesian estimators which take into account the prior knowledge of the signal distribution outperform and improve substantially the performance of the non-Bayesian estimators.

Le développement des antennes modales, qui sont des antennes actives reconfigurables en diagramme de rayonnement mais pas en réseaux, a commencé pour pouvoir implémenter le dépointage électronique dans les téléphones portables. Cette solution est généralement réalisée par un réseau d’antennes, ce qui est très difficile, voire impossible, dans un téléphone portable. Le dépointage permettrait d’améliorer le bilan de liaison et d’augmenter le débit des données.Le premier objectif de cette thèse est donc de développer des antennes modales pour la norme LTE. Trois concepts d’antennes modales ont été présentés. Le premier est une antenne de type « folded loop » active reconfigurable par permutation des points d’alimentation et de retour à la masse. Le deuxième propose une architecture pour rassembler l’antenne principale et l’antenne diversité en bas du téléphone, tout en supportant le MIMO et l’agrégation de porteuses, deux des spécificités de la LTE. Le dernier optimise l’utilisation de la seconde antenne des systèmes LTE MIMO pour procéder au dépointage électronique.Ces antennes modales ne peuvent délivrer leur réel potentiel qu’en étant utilisées avec un algorithme de pilotage, qui choisira la configuration ou le mode approprié(e) à la situation. Le second objectif de cette thèse est donc le développement d’algorithmes intelligents de pilotage d’antennes modales. Le premier algorithme développé et breveté par la société Ethertronics a la particularité de prédire à chaque instant quel sera le meilleur mode à l’instant suivant, à l’aide de données en bande de base pour la LTE. Le second algorithme est déterministe et permet d’estimer et de suivre la direction d’arrivée du signal. Il sélectionne ensuite le mode qui possède le meilleur gain dans cette direction, dans le but d’améliorer le bilan de liaison. / The development of modal antennas which are radiation pattern reconfigurable active antennas, but not arrays, started in order to implement beam forming in cellphones. This solution is generally made with an antenna array, which is very difficult, even impossible, in a mobile phone. Beam forming could improve the link budget and increase the data rate. The first aim of this thesis is the development of modal antennas for LTE standard. Three modal antennas concepts were presented. The first one is a reconfigurable “folded loop” active antenna by permutation of feed and ground points. The second one is a solution to gather the main and the diversity antenna in the bottom part of the phone, and to support MIMO and carrier aggregation, which are two features of LTE. The last one optimizes the use of the second antenna in LTE MIMO systems in order to perform beam forming. These modal antennas will provide their real potential only by being used by a driving algorithm which will choose the best mode or configuration according to the situation. So, the second aim of this thesis is the development of smart modal antenna driving algorithms. The first algorithm, developed and patented by Ethertronics, has the specificity to predict, at each moment, which mode will be the best for the next moment, by using baseband data for LTE. The second algorithm is deterministic and can estimate and track the direction of arrival of the signal. Then, it selects the mode which has the best gain in this direction in order to improve the link budget.

No description available.

En environnements hostiles, les signaux GNSS (Global Navigation Satellite System)peuvent être soumis à des risques de brouillages intentionnels. Basées sur un réseau d'antennes adaptatif, les solutions spatio-temporelles (STAP) ont déjà montré de bonnes performances de réjection des interférences. Toutefois, lorsque le module GNSS est placé sous les pales d'un hélicoptère, des effets non-stationnaires, appelés Rotor Blade Modulation (RBM), créés par les multiples réflexions du signal sur les pales du rotor, peuvent dégrader les techniques usuelles d’antibrouillage. Le signal utile GNSS n’est alors plus accessible. Le travail de la thèse consiste donc à élaborer un système de protection des signaux GNSS adapté à la RBM. Pour cela, un modèle innovant de multitrajets, adapté à ce type de phénomène, a été développé. La comparaison de simulations électromagnétiques représentatives et de mesures expérimentales sur hélicoptère EC-120 a permis de valider ce modèle. Celui-ci permet d'estimer, par maximum de vraisemblance, les paramètres de la contribution non-stationnaire du signal reçu. Enfin, l'association d'un algorithme de filtrage des multitrajets par projection oblique et d'un traitement STAP permet d'éliminer la contribution dynamique puis statique de l'interférence. Les simulations montrent que le signal utile GNSS est alors de nouveau exploitable. / In hostile environments, Global Navigation Satellite System (GNSS) can be disturbed by intentional jamming. Using antenna arrays, space-time adaptive algorithm (STAP) isone of the most efficient methods to deal with these threats. However, when a GNSS receiver is placed near rotating bodies, non-stationary effects called Rotor Blade Modulation (RBM) are created by the multipaths on the blades of the helicopter. They can degrade significantly the anti-jamming system and the signal of interest could belost. The work of the thesis is, consequently, to develop a GNSS protection system adapted to the RBM. In this way, an innovative multipath model, adapted to this phenomenon, has been developed. The model is then confirmed by comparison with a symptotic electromagnetic simulations and experiments conducted on an EC-120helicopter. Using a Maximum Likelihood algorithm, the parameters of the non-stationary part of the received signal have been estimated. And finally, the RBM anti-jamming solution, combining oblique projection algorithm and academic STAP, can mitigate dynamic and static contributions of interferences. In the end, the navigation information is available again.