Nonlinear attitude estimation based on fusion of inertial and magnetic sensors: Bio-logging application

AbstractThe aim of this paper concerns the 3D motion estimation problem using low-cost sensors fusion. This work will be applied in Bio-logging which is an interdisciplinary research area at the intersection of animal behavior and bioengineering. It refers to the use of miniaturized adapted-animal systems for logging and/or relaying of data about an animal's movements, physiology and/or environment. Generally, accurate attitude measurements are obtained using accelerometer and magnetometer, but at low frequencies movements. Then, to improve the performance and precision of the attitude estimation at high frequencies, we propose to add gyroscope and to develop an approach relaying on a quaternion-based nonlinear filter for the tracking of rigid body attitude (orientation) and heading. The algorithm fuses data from low-pass sensors such as 3-axis accelerometer, 3-axis magnetometer and high-pass sensor such as 3-axis gyroscope. Then, we exploit the sensor readings directly in the designed filter which lead to increase the computational requirements. Finally, the proposed approach is illustrated by an attitude estimation example in an experimental case of noisy measurements which shows the efficiency of the proposed algorithm.