AbstractsPsychology

Pedestrian navigation system using shoe-mounted INS

by Yan Li




Institution: University of Technology, Sydney
Department:
Year: 2014
Record ID: 1069332
Full text PDF: http://hdl.handle.net/10453/34395


Abstract

Pedestrian navigation using Global Positioning System (GPS) is still a considerable challenge in indoor environments where GPS signals are blocked. Inertial Navigation System (INS) is a self-contained system which can offer a navigation solution in most environments without the need for any additional infrastructures. A type of pedestrian navigation system with shoe-mounted Inertial Measurement Units (IMUs) has shown promising results. During walking, the foot is briefly stationary at zero velocity on the ground, named as the stance phase. The technique zero velocity update (ZUPT) is implemented to constrain the sensors’ error which uses the stance phase in each step to provide corrections periodically. In this research, a model with 24 error states is applied to correct IMU errors with an Extended Kalman Filter (EKF). The EKF estimated velocity errors are reset to zero in each stance phases, and successively to correct the IMU measurements. These repeated corrections could effectively control the error growth in navigation solution and minimize the drift. This thesis introduces three main contributions I have achieved for pedestrian navigation system with shoe-mounted IMU. Firstly, I have developed a new approach to detect the stance phase of different gait styles, including walking, running and stair climbing. Secondly, I have proposed a new concept called constant velocity update (CUPT) which is an extension of ZUPT to correct IMU errors on a moving platform with constant velocity, such as elevators or escalators. This new concept has broadened the practical application of pedestrian navigation based on shoe-mounted IMUs in a modern building environment. Lastly, as ZUPT applied at each step will lead to sharp corrections and discontinuities in the estimated trajectory, I developed a closed-loop step-wise smoothing algorithm to eliminate sharp corrections and smooth the trajectory. A software package in MATLAB has been developed and tested on different subjects. Good pedestrian navigation solutions have been achieved with the proposed method, which are published in journal and conference papers.