Estimation of Pedestrian Altitude Inside a Multi-Story Building Using an Integrated Micro-IMU and Barometer Device

Yuliang Zhao,Xiaopeng Sha,Hongjun Duan,Guangyi Shi,Jianing Yu,Wen J. Li,Jiaqi Liang

doi:10.1109/access.2019.2924664

Abstract

This paper presents a novel method of estimating the altitude of pedestrians who are walking in the indoor environment of a multi-story building. We will show that to achieve pedestrian altitude estimation, a pedestrian only needs to wear a small MEMS-based integrated sensing device consisting of a micro-IMU (i.e., consists of a 3D accelerometer, a 3D gyroscope, and a 3D magnetometer) and a barometer, during indoor activities. High-precision estimates of the pedestrian's position in the vertical direction were obtained by utilizing the acceleration and angular rate data, as well as the height, deduced from barometer data. The inherent drifts of the IMU sensors, which lead to cumulative errors in altitude estimation, were sharply reduced using a complementary filter and an error compensation algorithm. The experimental results demonstrate that this method is effective in reducing estimation errors. When a person walks on stairs with the same step height, the error of the estimated height of each step is within 0.5 cm, and the cumulative height error is about 1.7% over a total height of 2.9 m. This integrated sensing device also exhibits good stability, i.e., three 20-min tests in a 12-h period showed that the cumulative error accounts for about 2% of the total height of 11.23 m. When the stairs have different heights, i.e., heights ranging from 12 to 28 cm, the estimated height error of each step is within 2 cm. With an ability to provide accurate and reliable vertical altitude estimates of pedestrians inside a multi-story building, the sensing device developed through this paper is suitable for use in 3D-space body tracking and pedestrian navigation applications.

Highlights

Walking is an important and basic motion of the human body
Using a Target-error Compensation (TC) algorithm on these two estimated heights, our method sharply reduced the inherent drifts of Inertial Measurement Unit (IMU) sensors and ensured highprecision altitude estimation of pedestrians walking inside a multi-story building
To reduce the drift error of the IMU, the accelerations in the stance were corrected by updating the acceleration to zero and the accelerations in swing phases were corrected by the complementary filter

Summary

INTRODUCTION

Walking is an important and basic motion of the human body. It generates a large amount of useful information of our body relative to the environment. (1) Prior work using multiple MEMS sensor nodes Utilizing the relative motion of the body joints, multisensor-based methods were developed to reduce the error of the estimated altitude. We have shown that a sensing device integrated with MEMS micro-IMU and barometer could be used to estimate pedestrian altitude, and long-time sensing stability could be achieved, i.e., it provides stable altitude estimation results in 12-hours testing, even in environments with variable step heights of stairs. Our altitude estimating method has three main advantages: using only one sensor node, corrected drifts of IMU data, and compensated target height. Using a Target-error Compensation (TC) algorithm on these two estimated heights, our method sharply reduced the inherent drifts of IMU sensors and ensured highprecision altitude estimation of pedestrians walking inside a multi-story building

SYSTEM OVERVIEW AND DATA CORRECTION

ALTITUDE ESTIMATION

Findings

CONCLUSION