A modelagem computacional tem se tornado uma poderosa ferramenta utilizada mundialmente em pesquisas sobre sistemas de comunicação móvel. Em tais sistemas, a modelagem do canal é fator indispensável, pois as características de mobilidade e propagação presentes nesse tipo de sistema são responsáveis por distorções ocorridas sobre o sinal transmitido. O presente trabalho reúne os principais modelos matemáticos e computacionais de canal de comunicação móvel. Realiza-se uma abordagem histórica sobre o assunto, apresentado a natureza do problema do desvanecimento e a forma como foi modelado inicialmente. Por outro lado, apresentam-se modelos recentes, considerados eficazes do ponto de vista matemático e eficientes do ponto de vista computacional. O trabalho traz como contribuição a proposta de um novo modelo de canal com desvanecimento. Os modelos apresentados foram analisados do ponto de vista matemático por meio de suas propriedades estatísticas. Do ponto de vista numérico e computacional a análise se deu por meio de simulações. A principal conclusão obtida mostra que dois modelos com filtragem no domínio da freqüência, sendo um deles o novo modelo proposto, são os mais indicados para simular formas de onda que representem um canal com desvanecimento Rayleigh. Este trabalho tem a pretensão de ser útil para pesquisadores atuantes na área de modelagem e simulação de sistemas atuais de comunicação móvel. / Computational modelling is a powerful and widely used tool for research in mobile communication systems. In such systems, the communication channel modelling is an indispensable factor, because its mobility and propagation characteristics can cause distortion over the transmitted waveform. This work contains the main mathematical and computing communication channel models. A historical cover is provided, which presents the nature of the problem and the initial modelling of the fading phenomenon. On the other hand, recent models are presented, which are mathematically effective and computationally efficient. One contribution of this work is the proposal of a new fading channel computational model, which was suitably tested and validated. The presented models were mathematically analyzed through its statistical properties. From numerical and computational point of view, the models were analyzed through several simulations. The main conclusion, from analytical and simulated results, shows that two models using frequency filtering are the best choice for the generation of multiple uncorrelated Rayleigh fading waveforms, where one of them is the new proposed model. This work can help mobile communications researchers to suitably model the communication channel in a computer simulation.

This thesis studies the design and implementation of a linear minimum mean-square error (LMMSE) receiver in asynchronous bandlimited direct-sequence code-division multiple-access (DS-CDMA) systems that employ long-code pseudo-noise (PN) sequences and operate in multipath environments. The receiver is shown to be capable of multiple-access interference (MAI) suppression and multipath diversity combining without the knowledge of other users' signature sequences. It outperforms any other linear receiver by maximizing output signal-to-noise ratio (SNR) with the aid of a new chip filter which exploits the cyclostationarity of the received signal and combines all paths of the desired user that fall within its supported time span. This work is motivated by the shortcomings of existing LMMSE receivers which are either incompatible with long-code CDMA or constrained by limitations in the system model. The design methodology is based on the concept of linear/conjugate linear (LCL) filtering and satisfying the orthogonality conditions to achieve the LMMSE filter response. Moreover, the proposed LMMSE receiver addresses two drawbacks of the coherent Rake receiver, the industry's current solution for multipath reception. First, unlike the Rake receiver which uses the chip-matched filter (CMF) and treats interference as additive white Gaussian noise (AWGN), the LMMSE receiver suppresses interference by replacing the CMF with a new chip pulse filter. Second, in contrast to the Rake receiver which only processes a subset of strongest paths of the desired user, the LMMSE receiver harnesses the energy of all paths of the desired user that fall within its time support, at no additional complexity. The performance of the proposed LMMSE receiver is analyzed and compared with that of the coherent Rake receiver with probability of bit error, <i>Pe</i>, as the figure of merit. The analysis is based on the accurate improved Gaussian approximation (IGA) technique. Closed form conditional <i>Pe</i> expressions for both the LMMSE and Rake receivers are derived. Furthermore, it is shown that if quadriphase random spreading, moderate to large spreading factors, and pulses with small excess bandwidth are used, the widely-used standard Gaussian Approximation (SGA) technique becomes accurate even for low regions of <i>Pe</i>. Under the examined scenarios tailored towards current narrowband system settings, the LMMSE receiver achieves 60% gain in capacity (1. 8 dB in output SNR) over the selective Rake receiver. A third of the gain is due to interference suppression capability of the receiver while the rest is credited to its ability to collect the energy of the desired user diversified to many paths. Future wideband systems will yield an ever larger gain. Adaptive implementations of the LMMSE receiver are proposed to rid the receiver from dependence on the knowledge of multipath parameters. The adaptive receiver is based on a fractionally-spaced equalizer (FSE) whose taps are updated by an adaptive algorithm. Training-based, pilot-channel-aided (PCA), and blind algorithms are developed to make the receiver applicable to both forward and reverse links, with or without the presence of pilot signals. The blind algorithms are modified versions of the constant modulus algorithm (CMA) which has not been previously studied for long-code CDMA systems. Extensive simulation results are presented to illustrate the convergence behavior of the proposed algorithms and quantify their performance loss under various levels of MAI. Computational complexities of the algorithms are also discussed. These three criteria (performance loss, convergence rate, and computational complexity) determine the proper choice of an adaptive algorithm with respect to the requirements of the specific application in mind.

This thesis studies the design and implementation of a linear minimum mean-square error (LMMSE) receiver in asynchronous bandlimited direct-sequence code-division multiple-access (DS-CDMA) systems that employ long-code pseudo-noise (PN) sequences and operate in multipath environments. The receiver is shown to be capable of multiple-access interference (MAI) suppression and multipath diversity combining without the knowledge of other users' signature sequences. It outperforms any other linear receiver by maximizing output signal-to-noise ratio (SNR) with the aid of a new chip filter which exploits the cyclostationarity of the received signal and combines all paths of the desired user that fall within its supported time span. This work is motivated by the shortcomings of existing LMMSE receivers which are either incompatible with long-code CDMA or constrained by limitations in the system model. The design methodology is based on the concept of linear/conjugate linear (LCL) filtering and satisfying the orthogonality conditions to achieve the LMMSE filter response. Moreover, the proposed LMMSE receiver addresses two drawbacks of the coherent Rake receiver, the industry's current solution for multipath reception. First, unlike the Rake receiver which uses the chip-matched filter (CMF) and treats interference as additive white Gaussian noise (AWGN), the LMMSE receiver suppresses interference by replacing the CMF with a new chip pulse filter. Second, in contrast to the Rake receiver which only processes a subset of strongest paths of the desired user, the LMMSE receiver harnesses the energy of all paths of the desired user that fall within its time support, at no additional complexity. The performance of the proposed LMMSE receiver is analyzed and compared with that of the coherent Rake receiver with probability of bit error, <i>Pe</i>, as the figure of merit. The analysis is based on the accurate improved Gaussian approximation (IGA) technique. Closed form conditional <i>Pe</i> expressions for both the LMMSE and Rake receivers are derived. Furthermore, it is shown that if quadriphase random spreading, moderate to large spreading factors, and pulses with small excess bandwidth are used, the widely-used standard Gaussian Approximation (SGA) technique becomes accurate even for low regions of <i>Pe</i>. Under the examined scenarios tailored towards current narrowband system settings, the LMMSE receiver achieves 60% gain in capacity (1. 8 dB in output SNR) over the selective Rake receiver. A third of the gain is due to interference suppression capability of the receiver while the rest is credited to its ability to collect the energy of the desired user diversified to many paths. Future wideband systems will yield an ever larger gain. Adaptive implementations of the LMMSE receiver are proposed to rid the receiver from dependence on the knowledge of multipath parameters. The adaptive receiver is based on a fractionally-spaced equalizer (FSE) whose taps are updated by an adaptive algorithm. Training-based, pilot-channel-aided (PCA), and blind algorithms are developed to make the receiver applicable to both forward and reverse links, with or without the presence of pilot signals. The blind algorithms are modified versions of the constant modulus algorithm (CMA) which has not been previously studied for long-code CDMA systems. Extensive simulation results are presented to illustrate the convergence behavior of the proposed algorithms and quantify their performance loss under various levels of MAI. Computational complexities of the algorithms are also discussed. These three criteria (performance loss, convergence rate, and computational complexity) determine the proper choice of an adaptive algorithm with respect to the requirements of the specific application in mind.

Vehicular networking is envisioned to be a key technology area for significant growth in the coming years. Although the expectations for this emerging technology are set very high, many practical aspects remain still unsolved for a vast deployment of vehicular networks. This dissertation addresses the enabling physical layer techniques to meet the challenges in vehicular networks operating in mobile wireless environments. Considering the infrastructure-less nature of vehicular networks, we envision cooperative diversity well positioned to meet the demanding requirements of vehicular networks with their underlying distributed structure. Cooperative diversity has been proposed as a powerful means to enhance the performance of high-rate communications over wireless fading channels. It realizes spatial diversity advantages in a distributed manner where a node uses others antennas to relay its message creating a virtual antenna array. Although cooperative diversity has garnered much attention recently, it has not yet been fully explored in the context of vehicular networks considering the unique characteristics of vehicular networks, this dissertation provides an error performance analysis study of cooperative transmission schemes for various deployment and traffic scenarios. In the first part of this dissertation, we investigate the performance of a cooperative vehicle-to-vehicle (V2V) system with amplify-and-forward relaying for typical traffic scenarios under city/urban settings and a highway area. We derive pairwise error probability (PEP) expressions and demonstrate the achievable diversity gains. The effect of imperfect channel state information (CSI) is also studied through an asymptotical PEP analysis. We present Monte-Carlo simulations to confirm the analytical derivations and present the error rate performance of the vehicular scheme with perfect and imperfect-CSI. In the second part, we consider road-to-vehicle (R2V) communications in which roadside access points use cooperating vehicles as relaying terminals. Under the assumption of decode-and-forward relaying, we derive PEP expressions for single-relay and multi-relay scenarios. In the third part, we consider a cooperative multi-hop V2V system in which direct transmission is not possible and investigate its performance through the PEP derivation and diversity gain analysis. Monte-Carlo simulations are further provided to con firm the analytical derivations and provide insight into the error rate performance improvement.

Τα συστήματα που έχουν πολλαπλές κεραίες σε πομπό και δέκτη (ΜΙΜΟ) έχουν την δυνατότητα να επιτύχουν υψηλούς ρυθμούς δεδομένων και αυξημένη αξιοπιστία χωρίς να απαιτείται επιπλέον εύρος ζώνης ή ισχύς μετάδοσης. Η βασική αρχή στην οποία βασίζονται είναι ότι το σήμα που εκπέμπεται από τον πομπό διέρχεται από περισσότερα του ενός ανεξάρτητα κανάλια. Ο δέκτης εκμεταλλευόμενος τις πολλαπλές λήψεις του ίδιου σήματος μπορεί να βελτιώσει την απόδοσή του. Η εισαγωγή πολλαπλών κεραιών σε κάποια συστήματα δεν είναι δυνατό να συμβεί συνήθως λόγω του χώρου που απαιτείται. Παρόλα αυτά, σε αυτό το περιβάλλον επικοινωνίας υπάρχουν συνήθως πολλαπλοί χρήστες που μπορούν να συνεργαστούν και να δημιουργήσουν ένα κατανεμημένο σύστημα ΜΙΜΟ, που αναφέρεται στην βιβλιογραφία ως συνεργατικό (cooperative). Στα συστήματα MIMO έχουν προταθεί τεχνικές προσανατολισμένης επικοινωνίας (beamforming) με σκοπό την ακύρωση των παρεμβολών και του θορύβου στο δέκτη. Οι τεχνικές αυτές απαιτούν την γνώση της κατάστασης του καναλιού αφού πραγματοποιούν διάσπαση της μήτρας των συντελεστών του καναλιού κατά παράγοντες ώστε να εξάγουν τα διανύσματα βάρους με τα οποία θα πολλαπλασιάσουν τις ακολουθίες των συμβόλων που λαμβάνει ο δέκτης ή /και των συμβόλων που μεταδίδει ο πομπός. Συγκεκριμένα, μελετήθηκε η περίπτωση της τεχνικής προσανατολισμένης επικοινωνίας που στηρίζεται στην μέθοδο SVD η οποία πολλαπλασιάζει το διάνυσμα των προς μετάδοση συμβόλων στον πομπό και το διάνυσμα των ληφθέντων συμβόλων στο δέκτη με τα κατάλληλα ιδιάζοντα διανύσματα, επιτυγχάνοντας προσανατολισμένη επικοινωνία λήψης και εκπομπής (transmit και receive beamforming). Όπως αναφέρθηκε, η συγκεκριμένη μέθοδος απαιτεί την γνώση της κατάστασης του καναλιού σε πομπό και σε δέκτη. Για αυτό το σκοπό αρχικά θα μελετηθεί η επίδραση της εκτίμησης του καναλιού στην επίδοση της μεθόδου η οποία διεξάγεται από ένα εκτιμητή μέγιστης πιθανοφάνειας από ακολουθίες συμβόλων εκμάθησης που έχει μεταδώσει ο πομπός. Στην συνέχεια θα εξεταστεί η περίπτωση που τα κανάλια μπορούν να περιγραφούν από ένα μοντέλο πολλαπλών μονοπατιών. Ένα τέτοιο μοντέλο είναι δυνατό να εκτιμηθεί από δείγματα της κρουστικής απόκρισης του καναλιού, βελτιώνοντας περαιτέρω την επίδοση του συστήματος. Επίσης, παρέχει και την δυνατότητα της πρόβλεψης των μεταγενέστερων καταστάσεων του καναλιού, μειώνοντας αρκετά τον αριθμό των συμβόλων εκμάθησης που απαιτούνται. Η εκτίμηση των παραμέτρων του μοντέλου του καναλιού θα γίνει με την βοήθεια της μεθόδου ESPRIT. Τελικά, θα ενσωματωθεί η εκτίμηση του μοντέλου και στην τεχνική προσανατολισμένης επικοινωνίας και θα μελετηθεί η επίδοσή της. Στην συνέχεια θα εφαρμόσουμε την προηγούμενη διάταξη στην περίπτωση των συνεργατικών συστημάτων. Θα εφαρμοστεί λοιπόν, σε ένα τέτοιο σύστημα η τεχνική με την εκτίμηση του μοντέλου του καναλιού και θα αναλυθεί η επίδοσή του για τα δύο πιο γνωστά πρωτόκολλα επικοινωνίας μεταξύ του κόμβου-πηγής και των κόμβων-συνεργατών, το ενίσχυσης και προώθησης και το αποκωδικοποίησης και προώθησης. / The systems that have multiple transmit and receive antennas (MIMO) can achieve high data rates and increased reliability without the need for additional bandwidth or transmission power. The aforementioned is based on the transmission of the signal of the transmitter via multiple independent channels. The receiver can use the multiple versions of the same signal to improve its performance. The introduction of multiple antennas in some systems it is not possible due to the lack of space. On contrast, in a multi-user environment there are users of a single antenna that can cooperate to construct a distributed MIMO system, which are called in the bibliography as a cooperative system. A number of beamforming schemes have already proposed in MIMO systems with the view of interference and noise cancellation. These schemes compute the singular value decomposition of the channel matrix and use the singular vectors to extract the weight vectors that are used to multiply the sequences of symbols that transmitter transmits and the symbols that receiver receives. This scheme achieves transmit and receive beamforming and transmitter and receiver must have full channel state information (CSI). The next step is to examine the performance of this method under channel estimation errors. The estimation of the channel is carried out with a maximum likelihood estimator from training sequences that were transmitted from the transmitter. After that, we examine the case in which the channel taps can be modeled by a multipath model. The parameters of a model of this kind can be computed from noise corrupted samples with sub-space methods. In this thesis we use the ESPRIT method for the estimation of these parameters. After the estimation of the model’s parameters we can use the model to predict future values of channel taps, decreasing with this way the number of the training symbols that are needed. Then, we will use this method in the system with the beamforming scheme and we will evaluate its performance. Finally, the complete infrastructure will be applied to a cooperative system and its performance will be tested for the two most popular cooperation protocols, the amplify and forward protocol and the decode and forward protocol.

Nowadays, satellite-based localization is a well-established technical solution to support several navigation tasks in daily life. Besides the application inside of portable devices, satellite-based positioning is used for in-vehicle navigation systems as well. Moreover, due to its global coverage and the availability of inexpensive receiver hardware it is an appealing technology for numerous applications in the area of Intelligent Transportation Systems (ITSs). However, it has to be admitted that most of the aforementioned examples either rely on modest accuracy requirements or are not sensitive to temporary integrity violations. Although technical concepts of Advanced Driver Assistance Systems (ADASs) based on Global Navigation Satellite Systems (GNSSs) have been successfully demonstrated under open sky conditions, practice reveals that such systems suffer from degraded satellite signal quality when put into urban areas. Thus, the main research objective of this thesis is to provide a reliable vehicle positioning concept which can be used in urban areas without the aforementioned limitations. Therefore, an integrated probabilistic approach which preforms fault detection & exclusion, localization and multi-sensor data fusion within one unified Bayesian framework is proposed. From an algorithmic perspective, the presented concept is based on a probabilistic data association technique with explicit handling of outlier measurements as present in urban areas. By that approach, the accuracy, integrity and availability are improved at the same time, that is, a consistent positioning solution is provided. In addition, a comprehensive and in-depth analysis of typical errors in urban areas within the pseudorange domain is performed. Based on this analysis, probabilistic models are proposed and later on used to facilitate the positioning algorithm. Moreover, the presented concept clearly targets towards mass-market applications based on low-cost receivers and hence aims to replace costly sensors by smart algorithms. The benefits of these theoretical contributions are implemented and demonstrated on the example of a real-time vehicle positioning prototype as used inside of the European research project GAlileo Interactive driviNg (GAIN). This work describes all necessary parts of this system including GNSS signal processing, fault detection and multi-sensor data fusion within one processing chain. Finally, the performance and benefits of the proposed concept are examined and validated both with simulated and comprehensive real-world sensor data from numerous test drives.

Vehicular networking is envisioned to be a key technology area for significant growth in the coming years. Although the expectations for this emerging technology are set very high, many practical aspects remain still unsolved for a vast deployment of vehicular networks. This dissertation addresses the enabling physical layer techniques to meet the challenges in vehicular networks operating in mobile wireless environments. Considering the infrastructure-less nature of vehicular networks, we envision cooperative diversity well positioned to meet the demanding requirements of vehicular networks with their underlying distributed structure. Cooperative diversity has been proposed as a powerful means to enhance the performance of high-rate communications over wireless fading channels. It realizes spatial diversity advantages in a distributed manner where a node uses others antennas to relay its message creating a virtual antenna array. Although cooperative diversity has garnered much attention recently, it has not yet been fully explored in the context of vehicular networks considering the unique characteristics of vehicular networks, this dissertation provides an error performance analysis study of cooperative transmission schemes for various deployment and traffic scenarios. In the first part of this dissertation, we investigate the performance of a cooperative vehicle-to-vehicle (V2V) system with amplify-and-forward relaying for typical traffic scenarios under city/urban settings and a highway area. We derive pairwise error probability (PEP) expressions and demonstrate the achievable diversity gains. The effect of imperfect channel state information (CSI) is also studied through an asymptotical PEP analysis. We present Monte-Carlo simulations to confirm the analytical derivations and present the error rate performance of the vehicular scheme with perfect and imperfect-CSI. In the second part, we consider road-to-vehicle (R2V) communications in which roadside access points use cooperating vehicles as relaying terminals. Under the assumption of decode-and-forward relaying, we derive PEP expressions for single-relay and multi-relay scenarios. In the third part, we consider a cooperative multi-hop V2V system in which direct transmission is not possible and investigate its performance through the PEP derivation and diversity gain analysis. Monte-Carlo simulations are further provided to con firm the analytical derivations and provide insight into the error rate performance improvement.

De nombreuses solutions sont développées pour diminuer l'influence des multitrajets sur la précision et la disponibilité des systèmes GNSS. L'intégration de capteurs supplémentaires dans le système de localisation est l'une des solutions permettant de compenser notamment l'absence de données satellitaires. Un tel système est certes d'une bonne précision mais sa complexité et son coût limitent un usage très répandu.Cette thèse propose une approche algorithmique destinée à améliorer la précision des systèmes GNSS en milieu urbain. L'étude se base sur l'utilisation des signaux GNSS uniquement et une connaissance de l'environnement proche du récepteur à partir d'un modèle 3D du lieu de navigation.La méthode présentée intervient à l'étape de filtrage du signal reçu par le récepteur GNSS. Elle exploite les techniques de filtrage statistique de type Monte Carlo Séquentiels appelées filtre particulaire. L'erreur de position en milieu urbain est liée à l'état de réception des signaux satellitaires (bloqué, direct ou réfléchi). C'est pourquoi une information sur l'environnement du récepteur doit être prise en compte. La thèse propose également un nouveau modèle d'erreurs de pseudodistance qui permet de considérer les conditions de réception du signal dans le calcul de la position.Dans un premier temps, l'état de réception de chaque satellite reçu est supposé connu dans le filtre particulaire. Une chaîne de Markov, valable pour une trajectoire connue du mobile, est préalablement définie pour déduire les états successifs de réception des satellites. Par la suite, on utilise une distribution de Dirichlet pour estimer les états de réception des satellites / Most of the GNSS-based transport applications are employed in dense urban areas. One of the reasons of bad position accuracy in urban area is the obstacle's presence (building and trees). Many solutions are developed to decrease the multipath impact on accuracy and availability of GNSS systems. Integration of supplementary sensors into the localisation system is one of the solutions used to supply a lack of GNSS data. Such systems offer good accuracy but increase complexity and cost, which becomes inappropriate to equip a large fleet of vehicles.This thesis proposes an algorithmic approach to enhance the position accuracy in urban environment. The study is based on GNSS signals only and knowledge of the close reception environment with a 3D model of the navigation area.The method impacts the signal filtering step of the process. The filtering process is based on Sequential Monte Carlo methods called particle filter. As the position error in urban area is related to the satellite reception state (blocked, direct or reflected), information of the receiver environment is taken into account. A pseudorange error model is also proposed to fit satellite reception conditions. In a first work, the reception state of each satellite is assumed to be known. A Markov chain is defined for a known trajectory of the vehicle and is used to determine the successive reception states of each signal. Then, the states are estimated using a Dirichlet distribution

Les GNSS sont désormais largement présents dans le domaine des transports. Actuellement, la communauté scientifique désire développer des applications nécessitant une grande précision, disponibilité et intégrité.Ces systèmes offrent un service de position continu. Les performances sont définies par les paramètres du système mais également par l’environnement de propagation dans lequel se propagent les signaux. Les caractéristiques de propagation dans l’atmosphère sont connues. En revanche, il est plus difficile de prévoir l’impact de l’environnement proche de l’antenne, composé d’obstacles urbains. L’axe poursuivit par le LEOST et le LAGIS consiste à appréhender l’environnement et à utiliser cette information en complément de l’information GNSS. Cette approche vise à réduire le nombre de capteurs et ainsi la complexité du système et son coût. Les travaux de recherche menés dans le cadre de cette thèse permettent principalement de proposer des modélisations d'erreur de pseudodistances et des modélisations de l'état de réception encore plus réalistes. Après une étape de caractérisation de l’erreur, plusieurs modèles d’erreur de pseudodistance sont proposés. Ces modèles sont le mélange fini de gaussiennes et le mélange de processus de Dirichlet. Les paramètres du modèle sont estimés conjointement au vecteur d’état contenant la position grâce à une solution de filtrage adaptée comme le filtre particulaire Rao-Blackwellisé. L’évolution du modèle de bruit permet de s'adapter à l’environnement et donc de fournir une localisation plus précise. Les différentes étapes des travaux réalisés dans cette thèse ont été testées et validées sur données de simulation et réelles. / Today, the GNSS are largely present in the transport field. Currently, the scientific community aims to develop transport applications with a high accuracy, availability and integrity. These systems offer a continuous positioning service. Performances are defined by the system parameters but also by signal environment propagation. The atmosphere propagation characteristics are well known. However, it is more difficult to anticipate and analyze the impact of the propagation environment close to the antenna which can be composed, for instance, of urban obstacles or vegetation.Since several years, the LEOST and the LAGIS research axes are driven by the understanding of the propagation environment and its use as supplementary information to help the GNSS receiver to be more pertinent. This approach aims to reduce the number of sensors in the localisation system, and consequently reduces its complexity and cost. The work performed in this thesis is devoted to provide more realistic pseudorange error models and reception channel model. After, a step of observation error characterization, several pseudorange error models have been proposed. These models are the finite gaussian mixture model and the Dirichlet process mixture. The model parameters are then estimated jointly with the state vector containing position by using adapted filtering solution like the Rao-Blackwellized particle filter. The noise model evolution allows adapting to an urban environment and consequently providing a position more accurate.Each step of this work has been tested and evaluated on simulation data and real data.

Dans les décennies à venir, la connaissance d’informations très précises concernant la position d’un objet permettra de créer des applications révolutionnaires dans les domaines sociaux, médicaux, commerciaux et militaires. La technologie Ultra-Wideband (UWB) est considérée comme un bon candidat permettant de fournir des capacités de localisation précise grâce à la mesure de l’estimation du temps d'arrivée (TOA). Dans cette thèse, des algorithmes de mesure de distance dans le cas multi-utilisateurs pour des systèmes UWB sont étudiés afin d'atteindre une bonne précision pour une faible complexité, avec de la robustesse aux interférences multi-utilisateur et dans le cas d’un grand nombre d'utilisateurs. Au cours de la dernière décennie, les signaux chaotiques ont reçu une attention significative en raison d'un certain nombre de caractéristiques intéressantes. Les signaux chaotiques sont des signaux non périodiques, déterministes ou considérés comme pseudo-aléatoires provenant de systèmes dynamiques non linéaires. Leur bonne autocorrélation et leurs faibles propriétés d’inter corrélation les rendent particulièrement résistants aux évanouissements par trajets multiples et capables d'atténuer les interférences multi-utilisateur (MUI). En raison de leur grande sensibilité aux conditions initiales, il est possible de générer un grand nombre de signaux chaotiques pour accroître la capacité globale du système. Dans cette thèse, deux nouveaux algorithmes d'estimation de TOA sont proposés dans un cadre multi-utilisateur avec une faible complexité et une bonne robustesse. Le nombre d'utilisateurs pris en charge par ces deux algorithmes est beaucoup plus grand que dans le cas des estimateurs de TOA actuels. Cependant, l'utilisation de séquences d'étalement classique et d’impulsion limite l'amélioration des performances et la capacité du système. Afin d’apporter des améliorations, des signaux chaotiques sélectionnés sont utilisés comme séquences d'étalement ou impulsion dans les algorithmes proposés. Grâce à l'utilisation de signaux chaotiques, notre algorithme est non seulement amélioré, mais permet également l’utilisation d’un plus grand nombre d'utilisateurs par comparaison avec l’algorithme utilisant des signaux classiques / In the coming decades, highly accurate position information has the potential to create revolutionary applications in the social, medical, commercial and military areas. Ultra-Wideband (UWB) technology is considered as a potential candidate for enabling accurate localization capabilities through Time-of-Arrival (TOA) based ranging techniques. Over the past decade, chaotic signals have received significant attention due to a number of attractive features. Chaotic signals are aperiodic, deterministic, and random-like signals derived from nonlinear dynamical systems whose good autocorrelation, low cross-correlation and sensitivity to the initial conditions make them particularly suitable to ranging systems. In this thesis, two new multiuser TOA estimation algorithms are proposed with low complexity and robustness to MUI, the number of users supported by which is much larger than current multiuser TOA estimators. While, the use of classic spreading sequences and ranging pulse constrain the further improvement of ranging performance and system capacity. For breaking through the limit brought by the classic signals, the selected chaotic signals are employed as the spreading sequences or ranging pulse in our proposed algorithms. With the use of chaotic signals, our proposed algorithm not only obtains the additional improvement, but also with capability to support larger number of users comparing with its counterpart using classic signals