الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Localization in an indoor environment is a very promising domain due to its many applications in many fields especially in human and robotic indoor navigation and tracking.
This thesis focuses on the development of an indoor positioning system based on con-sumer handheld devices. It reviews research in the domain of indoor positioning fol-lowed by a detailed discussion of a proposed system based on the sensor fusion of the wireless positioning data and the inertial measurement unit data.
Wireless positioning discussed is based on the widely used WiFi networks and is in-dependent of infrastructure variations or the need of a recalibration phase which is usually needed in most of wireless positioning technologies.
Inertial measurement data is used to calculate the mobile device position relative to an initial position by integrating the acceleration in a certain direction.
However, there are challenges for both wireless positioning and inertial sensors posi-tioning each on its own. For the wireless positioning, the main challenge is the high noise due to reflections and the distortion of the wireless signal. On the other hand, the inertial sensors drift due to the integration of noise leads to position errors on the long term. Sensor fusion techniques are introduced to enhance the performance of both positioning techniques combined.
Specifically, an estimation filtering algorithm is used for sensor fusion to calculate the position of the overall system. Simulated testing verified that sub-one-meter accuracy can be achieved, which is sufficient for indoor navigation systems.
Also, the proposed technique is promising for future indoor navigation systems that can be scalable and require minimal infrastructure installation depending on the avail-able wireless signals in the indoor environment.