@inbook{42d6ab5d8e384c5bab5afaae7713b9ae,
title = "Naive Kalman filtering for 3D object orientation",
abstract = "In the paper Naive Kalman filter is introduced and presented for estimating orientation in 3D space. Using the assumption of Bayesian classification systems, the angular velocity vector is treated as three separate events. Therefore, three independent Kalman filters are used to estimate Euler angles for each RPY coordinate system. Data fusion is presented for real IMU sensor which integrated data from triaxial gyroscope, accelerometer and magnetometer.",
keywords = "3D orientation, IMU, Innovative simulation systems, Kalman filter",
author = "Robert Bieda and Rafal Grygiel and Adam Galuszka",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.",
year = "2016",
doi = "10.1007/978-3-319-21118-3\_23",
language = "English",
series = "Studies in Systems, Decision and Control",
publisher = "Springer International Publishing",
pages = "399--410",
booktitle = "Studies in Systems, Decision and Control",
address = "Switzerland",
}