2D/3D indoor navigation based on multi-sensor assisted pedestrian navigation in Wi-Fi environments

Because of the complementary nature of inertial measurement unit based pedestrian dead reckoning (PDR) and Wi-Fi positioning, the combination of both systems yields a synergetic effect resulting in higher navigation performance. Barometric sensors can provide height information for 2D/3D indoor navigation applications in multi-floor environments. In this paper, we explore the multi-sensor assisted pedestrian navigation. A PDR/Wi-Fi/barometer integrated system is presented. The adaptive Kalman filter is employed for sensor fusion, which can adapt dynamic noise statistics. One field experiment has been conducted in a multi-floor building. The numerical results are presented to show the navigation performance of the integrated system.