A smartphone localization algorithm using RSSI and inertial sensor measurement fusion

• Main Authors: Li, William Wei-Liang (Author), Iltis, Ronald A. (Author), Win, Moe Z. (Contributor)
• Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2015-06-08T14:41:35Z.
• Subjects: Article
• Online Access: Get fulltext

Indoor navigation using the existing wireless infrastructure and mobile devices is a very active research area. The major challenge is to leverage the extensive smartphone sensor suite to achieve location tracking with high accuracy. In this paper, we develop a navigation algorithm which fuses the WiFi received signal strength indicator (RSSI) and smartphone inertial sensor measurements. A sequential Monte Carlo filter is developed for inertial sensor based tracking, and a radiolocation algorithm is developed to infer mobile location based on RSSI measurements. The simulation results show that the proposed algorithm significantly outperforms the extended Kalman filter (EKF), and achieves competitive location accuracy compared with the round trip time (RTT) based ultra-wideband (UWB) system.
National Science Foundation (U.S.) (Grant ECCS-0901034)
United States. Office of Naval Research (Grant N00014-11-1-0397)
Defense University Research Instrumentation Program (U.S.) (Grant N00014-08-1-0826)
Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies