Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs

Sensors

Roberto G. Valenti²  Ivan Dryanovski¹  Jizhong Xiao² 

[1] The Graduate Center, The City University of New York, 365 Fifth Avenue, New York, NY 10016, USA; E-Mail:;The City College of New York, The City University of New York, Convent Avenue and 140th Street, New York, NY 10031, USA; E-Mail:

关键词: orientation estimation;    inertial measurement unit;    magnetic angular rate and gravity;    quaternions;    micro aerial vehicles;   

DOI  :  10.3390/s150819302

来源: mdpi

【 摘 要 】

Orientation estimation using low cost sensors is an important task for Micro Aerial Vehicles (MAVs) in order to obtain a good feedback for the attitude controller. The challenges come from the low accuracy and noisy data of the MicroElectroMechanical System (MEMS) technology, which is the basis of modern, miniaturized inertial sensors. In this article, we describe a novel approach to obtain an estimation of the orientation in quaternion form from the observations of gravity and magnetic field. Our approach provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. We separate the problems of finding the “tilt” quaternion and the heading quaternion in two sub-parts of our system. This procedure is the key for avoiding the impact of the magnetic disturbances on the roll and pitch components of the orientation when the sensor is surrounded by unwanted magnetic flux. We demonstrate the validity of our method first analytically and then empirically using simulated data. We propose a novel complementary filter for MAVs that fuses together gyroscope data with accelerometer and magnetic field readings. The correction part of the filter is based on the method described above and works for both IMU (Inertial Measurement Unit) and MARG (Magnetic, Angular Rate, and Gravity) sensors. We evaluate the effectiveness of the filter and show that it significantly outperforms other common methods, using publicly available datasets with ground-truth data recorded during a real flight experiment of a micro quadrotor helicopter.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.