A MEMS multi-sensors system for pedestrian navigation

Yuan Zhuang, Hsiu Wen Chang, Naser El-Sheimy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Micro-electro-mechanical system (MEMS) sensors are widely used in many applications due to their low cost, low power consumption, small size and light weight. Such MEMS sensors which are usually called multi-sensors include accelerometers, gyroscopes, magnetometers and barometers. In this research, Samsung Galaxy Note is used as the MEMS multi-sensors platform for pedestrian navigation. It contains a three-axis accelerometer, a three-axis gyroscope, a three-axis magnetometer and GPS receiver. Pedestrian Dead Reckoning (PDR) algorithms which include step detection, stride length estimation, heading estimation and PDR mechanization are carefully discussed in this paper. GPS solution is the major aiding source to reduce the MEMS IMU position, velocity and attitude errors when GPS signals are available. Magnetometers are also used to reduce the attitude errors of gyroscopes if there are no environment disturbances. A loosely-coupled extended Kalman Filter is implemented in the paper to fuse all the information to obtain the position result. Two typical scenarios are tested and analyzed in this paper: walking from outdoor to indoor and indoor walking. The MEMS multi-sensors system works well for both scenarios. To conclude, algorithms of MEMS multi-sensors system can provide an accurate, reliable and continuous result for pedestrian navigation on the platform of smart phone.

Original languageEnglish
Title of host publicationChina Satellite Navigation Conference, CSNC 2013 - Proceedings
Subtitle of host publicationPrecise Orbit Determination and Positioning - Atomic Clock Technique and Time-Frequency System - Integrated Navigation and New Methods
Pages651-660
Number of pages10
DOIs
Publication statusPublished - 2013 Aug 1
Event4th China Satellite Navigation Conference, CSNC 2013 - Wuhan, China
Duration: 2013 May 132013 May 17

Publication series

NameLecture Notes in Electrical Engineering
Volume245 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

Other4th China Satellite Navigation Conference, CSNC 2013
CountryChina
CityWuhan
Period13-05-1313-05-17

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

Fingerprint Dive into the research topics of 'A MEMS multi-sensors system for pedestrian navigation'. Together they form a unique fingerprint.

Cite this