Novel MEMS-IMU / Wi-Fi Integrated Indoor Pedestrian Location Algorithm

IIndoor pedestrian location technology has been in focus because of the development in indoor positioning and navigation system. The focus is placed on how to reduce the time and economic costs by ensuring the positioning accuracy and positioning performance of the system. By utilizing Mi-cro Electromechanical Systems -Inertial Measurement Unit (MEMS-IMU) in smart phones, this manuscript develops an integration strategy to directly estimate pedestrian location by combining MEMS-IMU and Wireless Fidelity (Wi-Fi) data. The work includes: 1) position estimation model relative to the reference coordinate system is established based on Pedestrian Dead Reckoning (PDR) algorithm; 2) gyroscope output in IMU is directly used as the original observation value, Wi-Fi positioning data is acquired at fixed frequency for system correction, and Extended Kalman Filter (EKF) algorithm is designed for estimating the real-time position coordinates of pedestrian; 3) the motion trajectory of pedestrians is designed, and algorithm efficacy and feasibility are verified by collecting the mobile phone sensors data and wireless signal Access Point (AP).