Scientific paper ID 2290 : 2022/3

Emil Iontchev1), Rosen Miletiev2), Todor Todorov1), Lachezar Hristov1), Emil Mihaylov1)

Determining the orientation of an object in space is a challenge that is encountered in many areas of human life - air transport, drone control, military technology, robotics, computer games, indoor positioning, etc.

In this article, a model of Kalman filter is proposed for determining object orientation based on inertial sensors and magnetometer. The state variables are specified and the observation parameters are selected. The inertial measurement module for absolute orientation BNO055 from Bosch was used to obtain the d parameters for the filter. The capability provided by the module was used to separate the gravity component of the measured acceleration from the accelerometer. This makes it possible to calculate orientation angles more accurately and under dynamic influences on the object. The magnetometer from the module was used to determine the angle of rotation about an axis parallel to the earth”s acceleration. Quaternions were directly obtained from BNO055 and used, as state variables, to predict the future state of the model. The filter is developed in the Matlab programming environment. To accurately set the orientation of an object in laboratory conditions and for the purpose of testing the filter, a device for setting the tilt relative to the initial vertical position was developed. A measurement system with BNO055 has been successfully implemented and experimental results for object orientation with the proposed Kalman filter have been obtained.

филтър на Калман акселерометър жироскоп магнитометър инерциална измервателна единица ъгли на Ойлер кватерниониKalman filter accelerometer gyroscope magnetometer inertial measurement unit Euler angles quaternionsEmil Iontchev) Rosen Miletiev) Todor Todorov) Lachezar Hristov) Emil Mihaylov)


[1] Vitali Andrea, Tilt computation using accelerometer data for inclinometer applications, November 2020, DT0140 Rev 1 1/19,

[2] Caruso Michael J. , Applications of Magnetic Sensors for Low Cost Compass Systems, Honeywell, SSEC

[3] Rate Gyro Application Note, Grossbow

[4] Kalman R. E., A New Approach to Linear Filtering and Prediction Problems, ASME Journal of Basic Engineering, series D: 35–45, 1960


[6] Welch Greg, Gary Bishop, An Introduction to the Kalman Filter, University of North Carolina at Chapel Hill, Department of Computer Science, NC 27599-3175,{welch, gb}

[7] Ozyagcilar Talat, Implementing a Tilt-Compensated eCompass using Accelerometer and Magnetometer Sensors, Freescale Semiconductor, Application Note Document Number:135 AN4248, Rev. 4.0, 11/2015

[8] Kim Phil, Kalman Filter for Beginners with Matlab Examples, A-JIN Publishing company, 2011, ISBN-13: 978-1463648350




This site uses cookies as they are important to its work.

Accept all cookies
Cookies Policy