الفهرس 
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Abstract
As a result of human spending most of his time in GPS-denied environments such as huge multi-storey buildings, the need fo human-tracking applications has been increased within those environments for many purposes such as navigation, guidance, emergency, etc., especially for their lack of GPS service. Many ways have emerged to track people in GPS denied environments that depend on WiFi or GSM Networks, Bluetooth and others. The use of smart phones in the last decade due to the tremendou development that occurred in their computing power, memory size, the number and types of sensors that are embedded in them, has encouraged the researchers to focus their attention on the denial of GPS areas. The trend has become to exploit the data collected from the sensors readings of the smartphone to provide a accurate tracking system while preserving energy in both indoor and outdoor environments In this thesis, we use the acquisition data obtained from the sensors on smart devices such as smartphones to build up a system that provides the users with the return way for their parked cars locations in the indoor garage of a multi-storey building where GPS is denied via tracking their paths inside the building using the Pedestrian Dead-Reckoning technique. Our approach harness the environment landmarks for floors separation and the PDR paths’ landmarks to enhance them by applying the Kalman Filter technique. Having done this step, we appended a trajectory pruning process to remove the redundant parts of the tracking trajectories as well as a trajectory reverse module to guide the users back to their car via some android applications.