GPS/Wi-Fi/ MEMS Sensors Integration for Indoor Navigation

In the last few years, pedestrian indoor navigation systems are widely used for various applications such as health care monitoring, Location Based Services (LBS) and emergency services. However, most of the indoor navigation systems are not mature, and could not provide continuous, accurate and reliable positioning solutions. GPS, MEMS sensors and Wi-Fi are three main candidate technologies for pedestrian navigation. GPS cannot provide reliable pedestrian navigation indoors because the GPS signals are degraded in indoor environments. MEMS sensors provide accurate but relative positioning solution for short time periods of standalone usages because of MEMS sensors’ errors characteristics. Wi-Fi can provide absolute location information by using pre-existing wireless infrastructures. However, Wi-Fi positioning requires special radio maps databases which is labour intensive and time consuming. Moreover, accurate orientation information from Wi-Fi cannot be provided in any of the existing methods. This research aims to improve the accuracy, reliability and accessibility of indoor navigation in two different ways for the current smart phones using GPS, Wi-Fi and MEMS sensors. Firstly, an algorithm is proposed to estimate the Wi-Fi heading by using clustering based and estimation based techniques.

Faculty Supervisor:

Naser El-Sheimy

Student:

Partner:

Trusted Positioning Inc

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Calgary

Program: