Investigating effective methods for integration of building's map with low cost inertial sensors and wifi-based positioning

In this paper a study has been made to investigate effective methods for utilizing building map information to complement indoor positioning using wifi positioning and inertial sensors. Two solutions have been developed which utilize Particle filter to integrate wifi positioning, inertial sensors and two different representations of the building map information. The first representation of the map information is a Computer Aided Drawing (CAD) that provides information of the walls inside a building. The information of the walls can be utilized for removing particles with impossible movements i.e. crossing walls. The second representation is a graph that provides information of the walkable areas inside a building. The motion of the user is constrained to the walkable areas only helping to remove the particles on the wrong trajectory. The performances of the developed solutions have been evaluated for the accuracy, consistency, number of particles and processing time needed for the calculation of the position estimate. Both of the developed solutions provide satisfactory performance. They run in real time on a tablet with dual core processor with mean error being less than 3m and consistency more than 90%. The analysis of the results indicates that the use of graphs in constraining the position estimate is an accurate and compact method for providing position aiding to the indoor positioning system based on wifi-positioning and inertial sensors.