Effects of initial attitude estimation errors on loosely coupled smartphone GPS/IMU integration system

Kwansik Park, Woohyun Kim, Jiwon Seo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Global Positioning System (GPS) and inertial measurement unit (IMU) sensors are commonly integrated using the extended Kalman filter (EKF), for achieving better navigation performance. However, because of nonlinearity, the performance of the EKF is affected by the initial state estimation errors, and the navigation solutions, including the attitude, diverge rapidly as the initial errors increase. This paper analyzes the data obtained from an outdoor experiment, and investigates the effect of the initial errors on the attitude estimation performance using EKF, which is used in loosely coupled low-cost smartphone GPS/IMU sensors.

Original languageEnglish
Title of host publication2020 20th International Conference on Control, Automation and Systems, ICCAS 2020
PublisherIEEE Computer Society
Pages800-803
Number of pages4
ISBN (Electronic)9788993215205
DOIs
Publication statusPublished - 2020 Oct 13
Event20th International Conference on Control, Automation and Systems, ICCAS 2020 - Busan, Korea, Republic of
Duration: 2020 Oct 13 → 2020 Oct 16

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2020-October
ISSN (Print)1598-7833

Conference

Conference20th International Conference on Control, Automation and Systems, ICCAS 2020
CountryKorea, Republic of
CityBusan
Period20/10/13 → 20/10/16

Bibliographical note

Funding Information:
This research was supported by the Unmanned Vehicles Core Technology Research and Development Program through the National Research Foundation of Korea (NRF) and the Unmanned Vehicle Advanced Research Center (UVARC) funded by the Ministry of Science and ICT, Republic of Korea (No. 2020M3C1C1A01086407).

Publisher Copyright:
© 2020 Institute of Control, Robotics, and Systems - ICROS.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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