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- Title
Novel MEMS-IMU / Wi-Fi Integrated Indoor Pedestrian Location Algorithm.
- Authors
Minghong Zhu; Ming Jin; Juan Liu; Zhenpeng Wang
- Abstract
Indoor 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 Micro 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).
- Subjects
INDOOR positioning systems; PEDESTRIANS; IEEE 802.11 (Standard); WIRELESS Internet; ALGORITHMS; SMARTPHONES; KALMAN filtering
- Publication
Engineering Letters, 2023, Vol 31, Issue 2, p774
- ISSN
1816-093X
- Publication type
Article