Collaborative Navigation in Fusion of Inertial Sensors and IoT Applications
Julang Ying, Ruojun Li, Liyuan Xu, Kaveh Pahlavan, Worcester Polytechnic Institute
Alternate Number 6
The idea of Internet of Things (IoT) has been widely spread and accepted recently. Since every object is connected and able to communicate with one another, we can expect that a new system of localization and navigation can be designed with higher accuracy. The commonly-used navigation system relies on the precision of Pedestrian Dead Reckoning (PDR), which is sensitive to the quality of signal collected from the inertial sensors. When IoT applications are introduced, where reliable RF information can be obtained, it is feasible to use these data in helping to localize the mobile terminal. In this paper, we proposed an infrastructure that can fuse the information from inertial sensors and IoT devices. Scenarios are designed at the third floor of Atwater Kent Laboratory in Worcester Polytechnic Institute, where 3 WiFi routers and 6 iBeacon Bluetooth Low Energy devices are deployed. Different sets of information are collected from an Android smartphone, while both Kalman and Particle Filter are tested and compared in collaborative localization accuracy. Extensive exploration is also made to look into the Cramer-Rao Lower Bound of the system, where the optimal localization precision can be determined.