With the rapid development of wireless networking technology and the great growth of service demand, accurate wireless location estimation has gained considerable attention. Most wireless location system may suffer from non-line-of-sight (NLOS) propagation error, which leads to a severe degradation of position accuracy. In this thesis, we propose a hybrid TOA/AOA (time of arrival/ angle of arrival) non-line-of-sight identification and wireless location technology to cope with NLOS condition. This algorithm can simultaneously determine the number of line-of-sight (LOS) base stations (BSs) and identify them. The identification part is to collect all TOA and AOA parameters from all BSs and to use residual information to detetmine whether the NLOS error is present in measurements. The localization method only processes the LOS measurements to avoid the NLOS error and increases position accurary. The simulation results show that the location system with TOA measurements can identify three or more LOS-BSs. The system has a high identification accuracy when the number of LOS-BSs is more than three. When the number of LOS-BSs is three, the degraded identification capability leads to larger position errors. When the AOA information is available in the positioning system, the TOA is combined with AOA because the property of the AOA localization method which needs only two measurements to locate the MS makes the location system capable of identifying two LOS-BSs. When the number of LOS-BSs is two, the combination of TOA and AOA measurements maintains a higher NLOS identification accuracy and make its location performance remarkably promoted.

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Inspired by promotion of commercial applications, support of location-based services to mobile terminals through their current location has been receiving a lot of attention in recent years even though emergency communications is the primary motivation for development of wireless location. A major challenge to wireless location technique is how to balance the implementation complexity and required accuracy. In the first part of this dissertation, we address one of the fundamental problems in wireless location when using the ToA measurements and develop a simple model to estimate the mobile terminal location with low complexity and promising accuracy. The model employs the geometrical transformation method with single propagation delay measurement. The contribution is that the use of geometrical transformation allows us to overcome the location handover problem, i.e., a forcing handover in a GSM (global system for mobile) network or a three-way soft handover in a UMTS (universal mobile telecommunications system) network. By using the proposed location model, the impact on network performance is kept at the minimum level and the complexity and requirements for hardware and software changes are reduced. In the second part of this dissertation, we address one of the fundamental problems in wireless location when using the SS (signal strength) measurements. The first contribution is to develop a novel wireless location technique based on a ¡§differ- encing¡¨ way, called the SSSD (stationary signal-strength-difference), to remove the uncertainty propagation parameters when merging environment-dependent signal propagation model into the location estimation. This is due to the uncertainty in propagation parameters causes a propagation model error that enlarges error in the distance estimation. The performance gained from the preliminary analysis of SSSD location technique, however, is degraded as a result of the large bias error in the estimated distance and distance difference. To achieve the performance enhancement, the second contribution is to correct the bias error in the estimated distance difference by using a correction method based on a geometric constraint condition. With the corrected distance difference, the final contribution is that we generalized the work on correction method and provide a new framework to correct the error in the estimated distance. As the corrected distance and distance difference is derived by LS (least square) computation, respectively, low computation burden and non-iterative solutions were achieved. To the best of our knowledge thus far, this is first such proposal for a correction to the SS-based location technique. It is demonstrated that the proposed error correction method is shown to perform well when encountering the large error in the estimated distance and distance difference, and prove that the location accuracy can be improved considerably.

In wireless location systems, received signals may be influenced by non-line of sight (NLOS) propagation errors, which yield severe degradation of location accuracy.Therefore, to distinguish how many measurement signals are line-of-sight (LOS) and to identify them simultaneously will contribute to the increase of location accuracy.We propose a method based on recursive hypothesis testing algorithm, and use residual information to determine whether the NLOS errors are present in measurements. Since the probability distribution of measurements with NLOS errors is different from that of measurements without NLOS errors, a likelihood ratio test can be used in determining the LOS/NLOS status of the measurements. To search for an optimal threshold for the hypothesis testing, particle filtering optimization(PFO) is adopted. The PFO algorithm uses particle filtering to find the best threshold for determining the status of signals measured at all base stations (BSs). In the PFO algorithm, the clustering property of K-means is also used in separating particles, thereby the search of optimal threshold may be implemented in parallel.In this thesis, we focus on the hybrid TOA/AOA (time of arrical/angle of arrival) location method, in which localization only uses the LOS location measurements to calculate the location of a mobile station. Simulation results show that the proposed algorithm performs better than other algorithms which suffer from different degrees of NLOS errors. The proposed scheme also obtains higher identification rate of LOS-BSs in different situations by using the optimal thresholds for status detection.

In the thesis, we propose a non-line of sight (NLOS) mitigation approach based on the interacting multiple model (IMM) algorithm. The IMM-based structure, composed of a biased Kalman filter (BKF) and a Kalman filter with NLOS-discarding process (KF-D), is capable of mitigating the ranging error caused by the NLOS effects, and therefore improving the performance and accuracy in wireless location systems. The NLOS effect on signal transmission is one of the major factors that affect the accuracy of the time-based location systems. Effective NLOS identification and mitigation usually count on pre-determined statistic distribution and hypothesis assumption in the signals. Because the variance of the NLOS error is much large than that of measurement noise, hypothesis testing on the LOS/NLOS status can be formulated.The BKF combines the sliding window and decides the status by using hypothesis testing. The calculated variance and the detection result are used in switching between the biased and unbiased modes in the Kalman filter. In the contrast, the KF-D scheme identifies the NLOS status and tries to eliminate the NLOS effects by directly using the estimated results from the LOS stage. The KF-D scheme can achieve reasonably good NLOS mitigation if the estimates in the LOS status are obtained. Due to the discarding process, changes of the state vector within the NLOS stage are possibly ignored, and will cause larger errors in the state estimates. The BKF and KF-D can make up for each other by formulating the filters in an IMM structure, which could tune up the probabilities of BKF and KF-D. In our approach, the measured data are smoothed by sliding window and a BKF. The variance of data and the hypothesis test result are passed to the two filters. The BKF switches between the biased/unbiased modes by using the result. The KF-D may receive the estimated value from BKF based on the results. The probability computation unit changes the weights to get the estimated TOA values. With the simulations in ultra-wideband (UWB) signals, it can be seen that the proposed IMM-based approach can effectively mitigate the NLOS effects and increase the accuracy in wireless position.

In response to a growing recognition of the importance of spatial information, the concept of Spatial Data Infrastructure (SDI) has evolved. Designed to facilitate an environment that promotes access and sharing of spatial information, SDI development has benefited from, and in due course adopted, advances in information technology (particularly improvements in desktop computing capabilities and communication networks such as the Internet). / The never ceasing progression of technology now enables communication and data access via mobile phones and a myriad of portable, networked computing devices. Indeed over the last few years, the proliferation of mobile phones has exceeded many expectations and is enabling nomadic users to communicate and access data services with ease. Location is one of the unique characteristics of mobility that is encompassed by this form of wireless communication and has been capitalised on in the form of enhanced safety initiatives. In turn, the infrastructure required for these safety services has encouraged additional Location Based Services (LBS) to flourish / LBS act as spatial decision making tools, providing information to end users based on their location, or on the location of some target. LBS are not restricted to the wireless environment however this is their current area of promotion. The principles of accessing spatial information that are encompassed by LBS mirror those of SDIs, and as a result SDI models need to accommodate for this new medium of information access and delivery. This research aimed to expand the SDI model to support applications that assist with spatial decision making, such as LBS. Focused specifically on LBS that are accessible for wirelessly networked, portable devices, this research implemented a theoretical and practical approach to identify the additional requirements for SDIs in this domain. A prototype LBS application for public transport information and navigation was developed and evaluated as part of this process. It is proposed that the resulting model (which details the additional requirements as well as their relative importance) act as an example framework for future LBS implementations so that they may gain the benefits from a standard, integrated infrastructure as offered by SDIs.

One of the major problems encountered in wireless location is the effect caused by non-line of sight (NLOS) propagation. When the direct path from the mobile station (MS) to base stations (BSs) is blocked by obstacles or buildings, the signal arrival times will delay. That will make the signal measurements include an error due to the excess path propagation. If we use the NLOS signal measurements for localization, that will make the system localization performance reduce greatly. In the thesis, a time-of-arrival (TOA) based location system with NLOS mitigation algorithm is proposed. The proposed method uses least squares-support vector machine (LS-SVM) with optimal parameters selection by particle swarm optimization (PSO) for establishing regression model, which is used in the estimation of propagation distances and reduction of the NLOS propagation errors. By using a weighted objective function, the estimation results of the distances are combined with suitable weight factors, which are derived from the differences between the estimated measurements and the measured measurements. By applying the optimality of the weighted objection function, the method is capable of mitigating the NLOS effects and reducing the propagation range errors. Computer simulation results in ultra-wideband (UWB) environments show that the proposed NLOS mitigation algorithm can reduce the mean and variance of the NLOS measurements efficiently. The proposed method outperforms other methods in improving localization accuracy under different NLOS conditions.

In wireless location system, geometric relationship between the base station (BS) and the mobile station (MS) may affect the accuracy of MS location estimate. The effect is called Geometric Dilution of Precision (GDOP). Given the information of geometric configuration of BS and MS locations, the GDOP value can be calculated accordingly. In fact, the GDOP value is considered as ratio factor between the location error and measurement noise. A higher GDOP value indicates larger location error in the location estimator. Therefore the GDOP can be utilized as an index for observing the location precision of the MS under different geometric layout. The accuracy of location estimation can be improved by changing the BS device element locations. In the thesis, a time different of arrival (TDOA) wireless location system with mobile base station (MBS) is considered. Changing the geometric layout between the BS and the MS by relocating the MBS, the GDOP effect can be reduced and the accuracy of location estimation also can therefore be improved. Since the simulated annealing (SA) is capable of escaping the local minimum and finding the global minimum in an objective function, the SA algorithm is used in finding the best solution in a defined function based on the GDOP distribution. The best solution is then the destination of an MBS in the process of MS location estimation. When relocating an MBS from its initial location to the best location, it is likely that the MBS enters regions with high GDOP effects. To avoid the problem, the steepest descent (SD) algorithm is utilized for path planning. First, we establish the objective function which consists of the GDOP information and the angle of movement. A nearby location that has the minimum value of objective function is selected as the next move. The process continues until the MBS reaches the destination. A variety of cases are investigated by computer simulations. Simulation results show that the proposed approach can effectively find the best locations for MBSs to relocate. Based on the relocation and path planning, the GDOP effects can be reasonably reduced, and therefore the higher location accuracy is achieved.

A vantagem das redes locais sem fios, as quais permitem que uma estação móvel possa deslocar-se livremente dentro da área de abrangência da rede, possui uma contrapartida em termos de segurança. A possibilidade dos sinais de microondas atravessarem paredes e sofrerem atenuação, reflexão, refração, difração e dispersão, dependendo dos obstáculos, torna a definição dos limites da área de abrangência da rede sem fios uma tarefa difícil. Sem o conhecimento dos limites de abrangência, o administrador não tem como delimitar fisicamente o acesso à rede. Além disso, o padrão IEEE 802.11 não define um mecanismo capaz de localizar a posição física de estações móveis. Sem a possibilidade de localização de estações, é impossível restringir o acesso à rede baseando-se em limitações físicas definidas pelo administrador. Quando a rede sem fios é utilizada em ambientes internos, os diversos obstáculos e seu comportamento dinâmico (como pessoas em movimento, por exemplo), fazem com que os sinais de microondas alterem as características da área de abrangência da rede. Este trabalho propõe uma nova abordagem para localização de estações sem fios em ambientes internos, baseada no comportamento dinâmico dos obstáculos e conseqüentes alterações na rede, e, de acordo com este comportamento, tenta ampliar a eficiência da localização de estações. Por fim, é proposto um novo sistema de autenticação de estações baseado na sua localização. / The advantage of wireless local area networks, giving the mobile stations the possibility of moving free inside the network access range comes with a security drawback. The fact that microwave signals can cross walls and behave with attenuation, reflections, refraction, diffraction and dispersion, depending of the obstacles, makes very difficult to define the network access range. Without the knowledge of the network boundaries, the network administrator cannot define a physical delimiter to network access. Besides this issue, there is no default user-location mechanism in the IEEE 802.11 standard. Without the user-location, it is impossible to restrict the network access based on the physical access boundaries defined by the administrator. When the wireless network operates indoor the many obstacles and the dynamic behavior of these obstacles (some people moving around, for instance) make the microwave signal behavior change the range and aspect of the network. This work proposes a new approach to indoor user-location mechanism, based on the dynamic behavior of the obstacles and consequent changes on network range. This approach focus on the dynamic obstacles behavior analysis and according to this behavior tries to increase the user-location system efficiency. Finally a new authentication system based on the user location is proposed.

A vantagem das redes locais sem fios, as quais permitem que uma estação móvel possa deslocar-se livremente dentro da área de abrangência da rede, possui uma contrapartida em termos de segurança. A possibilidade dos sinais de microondas atravessarem paredes e sofrerem atenuação, reflexão, refração, difração e dispersão, dependendo dos obstáculos, torna a definição dos limites da área de abrangência da rede sem fios uma tarefa difícil. Sem o conhecimento dos limites de abrangência, o administrador não tem como delimitar fisicamente o acesso à rede. Além disso, o padrão IEEE 802.11 não define um mecanismo capaz de localizar a posição física de estações móveis. Sem a possibilidade de localização de estações, é impossível restringir o acesso à rede baseando-se em limitações físicas definidas pelo administrador. Quando a rede sem fios é utilizada em ambientes internos, os diversos obstáculos e seu comportamento dinâmico (como pessoas em movimento, por exemplo), fazem com que os sinais de microondas alterem as características da área de abrangência da rede. Este trabalho propõe uma nova abordagem para localização de estações sem fios em ambientes internos, baseada no comportamento dinâmico dos obstáculos e conseqüentes alterações na rede, e, de acordo com este comportamento, tenta ampliar a eficiência da localização de estações. Por fim, é proposto um novo sistema de autenticação de estações baseado na sua localização. / The advantage of wireless local area networks, giving the mobile stations the possibility of moving free inside the network access range comes with a security drawback. The fact that microwave signals can cross walls and behave with attenuation, reflections, refraction, diffraction and dispersion, depending of the obstacles, makes very difficult to define the network access range. Without the knowledge of the network boundaries, the network administrator cannot define a physical delimiter to network access. Besides this issue, there is no default user-location mechanism in the IEEE 802.11 standard. Without the user-location, it is impossible to restrict the network access based on the physical access boundaries defined by the administrator. When the wireless network operates indoor the many obstacles and the dynamic behavior of these obstacles (some people moving around, for instance) make the microwave signal behavior change the range and aspect of the network. This work proposes a new approach to indoor user-location mechanism, based on the dynamic behavior of the obstacles and consequent changes on network range. This approach focus on the dynamic obstacles behavior analysis and according to this behavior tries to increase the user-location system efficiency. Finally a new authentication system based on the user location is proposed.