For the mass demands of wireless communication services, the mobile location technologies have drawn much attention of the governments, academia, and industries around the world. In wireless communication, one of the main problems with accurate location is nonline of sight (NLoS) propagation. To solve the problem, we present a new location algorithm with clustering technology by utilizing the geometrical feature of cell layout, time of arrival (ToA) range measurements, and three base stations. The mobile location is estimated by solving the optimal solution of the objective function based on the high density cluster. Simulations study was conducted to evaluate the performance of the algorithm for different NLoS error distributions and various upper bound of NLoS error. The results of our experiments demonstrate that the proposed algorithm is significantly more effective in location accuracy than range scaling algorithm, linear lines of position algorithm, and Taylor series algorithm, and also satisfies the location accuracy demand of E-911.

The ultra-wideband (UWB) technology has a vast unlicensed frequency spectrum, which can support precise indoor positioning in orders of centimeters. The features of UWB signals can be utilized for variety of applications. In this project first we present an empirical channel models to analyze the localization accuracy of the UWB technology for interactive electronic gaming (Ping-Pong) in Line-of-Sight (LOS) and Obstructed LOS (OLOS) scenarios. Then we introduce a new concept that we refer to as micro-gesture detection to handle the more refined motions of the hand, such as rotation, while one antenna is held by the user using features of UWB signal. We use four specific features of the UWB signals: time of arrival, power of the first peak, total power, and the Root-Mean Square (RMS) of the delay spread, for this purpose. As the hand rotates the position of the antenna in the hand and the external antenna changes from LOS to OLOS. We demonstrate that features of the UWB signals are more useful than the RSS signal of the Wi-Fi to detect this class of micro-gestures. We foresee this micro-gesture detection capabilities become helpful for the people with limited ability or visually impaired for implementation of simplified sign language to communication with electronic devices located away from a person. We compare gesture detection using multiple features of the UWB signal with traditional gesture detection using the received signal strength (RSS) of the Wi-Fi signal.

We consider time-of-arrival based robust geolocation in harsh line-of-sight/non-line-of-sight environments. Herein, we assume the probability density function (PDF) of the measurement error to be completely unknown and develop an iterative algorithm for robust position estimation. The iterative algorithm alternates between a PDF estimation step, which approximates the exact measurement error PDF (albeit unknown) under the current parameter estimate via adaptive kernel density estimation, and a parameter estimation step, which resolves a position estimate from the approximate log-likelihood function via a quasi-Newton method. Unless the convergence condition is satisfied, the resolved position estimate is then used to refine the PDF estimation in the next iteration. We also present the best achievable geolocation accuracy in terms of the Cramér-Rao lower bound. Various simulations have been conducted in both real-world and simulated scenarios. When the number of received range measurements is large, the new proposed position estimator attains the performance of the maximum likelihood estimator (MLE). When the number of range measurements is small, it deviates from the MLE, but still outperforms several salient robust estimators in terms of geolocation accuracy, which comes at the cost of higher computational complexity.

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

Spectrum, environment and location awareness are key characteristics of cognitive radio (CR). Knowledge of a user’s location as well as the surrounding environment type may enhance various CR tasks, such as spectrum sensing, dynamic channel allocation and interference management. This dissertation deals with the optimisation of adaptive localisation techniques for CR. The first part entails the development and evaluation of an efficient bandwidth determination (BD) model, which is a key component of the cognitive positioning system. This bandwidth efficiency is achieved using the Cramer-Rao lower bound derivations for a single-input-multiple-output (SIMO) antenna scheme. The performances of the single-input-single-output (SISO) and SIMO BD models are compared using three different generalised environmental models, viz. rural, urban and suburban areas. In the case of all three scenarios, the results reveal a marked improvement in the bandwidth efficiency for a SIMO antenna positioning scheme, especially for the 1×3 urban case, where a 62% root mean square error (RMSE) improvement over the SISO system is observed. The second part of the dissertation involves the presentation of a multiband time-of arrival (TOA) positioning technique for CR. The RMSE positional accuracy is evaluated using a fixed and dynamic bandwidth availability model. In the case of the fixed bandwidth availability model, the multiband TOA positioning model is initially evaluated using the two-step maximum-likelihood (TSML) location estimation algorithm for a scenario where line-of-sight represents the dominant signal path. Thereafter, a more realistic dynamic bandwidth availability model has been proposed, which is based on data obtained from an ultra-high frequency spectrum occupancy measurement campaign. The RMSE performance is then verified using the non-linear least squares, linear least squares and TSML location estimation techniques, using five different bandwidths. The proposed multiband positioning model performs well in poor signal-to-noise ratio conditions (-10 dB to 0 dB) when compared to a single band TOA system. These results indicate the advantage of opportunistic TOA location estimation in a CR environment. / Dissertation (MEng)--University of Pretoria, 2012. / Electrical, Electronic and Computer Engineering / unrestricted