CUED Publications database

Using inertial sensors for position and orientation estimation

Kok, M and Hol, JD and Schön, TB (2017) Using inertial sensors for position and orientation estimation. Foundations and Trends in Signal Processing, 11. pp. 1-153. ISSN 1932-8346

Full text not available from this repository.


In recent years, microelectromechanical system (MEMS) inertial sensors (3D accelerometers and 3D gyroscopes) have become widely available due to their small size and low cost. Inertial sensor measurements are obtained at high sampling rates and can be integrated to obtain position and orientation information. These estimates are accurate on a short time scale, but suffer from integration drift over longer time scales. To overcome this issue, inertial sensors are typically combined with additional sensors and models. In this tutorial we focus on the signal processing aspects of position and orientation estimation using inertial sensors. We discuss different modeling choices and a selected number of important algorithms. The algorithms include optimization-based smoothing and filtering as well as computationally cheaper extended Kalman filter and complementary filter implementations. The quality of their estimates is illustrated using both experimental and simulated data.

Item Type: Article
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 10 Dec 2017 20:10
Last Modified: 15 Apr 2021 06:20
DOI: 10.1561/2000000094