Emerging applications of location-based services have led to a growing interest in the use of positioning systems. Performance of the satellite-based GPS as the most popular positioning technique is degraded in indoor and urban environments due to visibility limits and multipath fading. Due to ever-growing coverage of WLAN networks, especially in indoor and metropolitan areas, integrating Wi-Fi and GPS has drawn attention, in academic research and industry, as a promising approach to solving problems encountered by precise indoor GPS positioning such as severe multipath.
This thesis investigates effective methods to integrate 802.11g WLAN signals with GPS in order to develop a seamless and robust positioning system especially in indoor environments. Towards this goal, the research presented in this thesis is first focused on the integration of WiFi and GPS in a context-aware framework for navigation filter adaption. A new two-layer multiple model adaptive estimation (MMAE) Kalman filtering algorithm is proposed where the parameters are adapted based on identified contexts using WiFi signals. The performance of the algorithm is assessed using real data to demonstrate positioning accuracy improvements. Secondly, this thesis investigates WiFi and GPS integration at the receiver level. To this end, a collaborative WiFi-based A-GPS scheme is proposed where 802.11g OFDM signals are used to provide fine time assistance for a reduced search space and a faster acquisition in challenging environments. The proposed scheme is primarily developed and tested for a controlled LOS environment using low complexity time domain OFDM timing techniques. The performance of the developed structure is subsequently evaluated in NLOS multipath environments. In order to improve the timing accuracy and robustness of the system in indoor multipath environments, an OFDM timing estimation method is proposed based on constrained Gaussian mixture modeling of the correlator output. The algorithm is tested for different multipath environments and the results demonstrate considerable performance improvements in terms of timing accuracy. It is shown that using the proposed timing method, the system is able to maintain its robustness in multipath environments under non-dominant direct path condition and for low SNR values.