A Novel 3D Pedestrian Navigation Method for a Multiple Sensors-Based Foot-Mounted Inertial System

A Novel 3D Pedestrian Navigation Method for a Multiple Sensors-Based Foot-Mounted Inertial System

Blog Article

In this paper, we present a novel method for 3D pedestrian navigation of foot-mounted inertial systems by integrating a MEMS-IMU, barometer, and permanent magnet.Zero-velocity update (ZUPT) is a well-known algorithm to eliminate Backpacks the accumulated error of foot-mounted inertial systems.However, the ZUPT stance phase detector using acceleration and angular rate is threshold-based, which may cause incorrect stance phase estimation in the running gait pattern.A permanent magnet-based ZUPT detector is introduced to solve this problem.

Peaks extracted from the magnetic field strength waveform are mid-stances of stance phases.A model of peak-peak information and stance phase duration is developed to have a quantitative calculation method of stance phase duration in different movement patterns.Height estimation using barometer is susceptible to the environment.A height difference information aided barometer (HDIB) algorithm integrating MEMS-IMU and barometer is raised to have a better height estimation.

The first stage of HDIB is to distinguish level ground/upstairs/downstairs and the second stage is to calculate height using reference atmospheric pressure obtained from the first stage.At last, a ZUPT-based adaptive average window length algorithm (ZUPT-AAWL) is proposed to calculate the true total travelled distance to have a more accurate percentage error (TTDE).This proposed method is verified via multiple Bulbs experiments.Numerical results show that TTDE ranges from 0.

32% to 1.04% in both walking and running gait patterns, and the height estimation error is from 0 m to 2.35 m.