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.
|Title of host publication||2020 20th International Conference on Control, Automation and Systems, ICCAS 2020|
|Publisher||IEEE Computer Society|
|Number of pages||4|
|Publication status||Published - 2020 Oct 13|
|Event||20th International Conference on Control, Automation and Systems, ICCAS 2020 - Busan, Korea, Republic of|
Duration: 2020 Oct 13 → 2020 Oct 16
|Name||International Conference on Control, Automation and Systems|
|Conference||20th International Conference on Control, Automation and Systems, ICCAS 2020|
|Country||Korea, Republic of|
|Period||20/10/13 → 20/10/16|
Bibliographical noteFunding 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).
© 2020 Institute of Control, Robotics, and Systems - ICROS.
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