Accurate IMU Based Orientation Estimation
Accurate IMU-Based Orientation Estimation Under
Conditions of Magnetic Distortion
Nagesh Yadav∗, Chris Bleakley†
{nagesh.yadav∗, chris.bleakley†}@ucd.ie
UCD Complex and Adaptive Systems Laboratory, UCD School of Computer Science and Informatics,
University College Dublin, Ireland
Abstract—Low cost, compact Inertial Measurement Units
(IMUs) are now being used to track human body movements in indoor environments by estimation of the 3D orientation of body segments. In many of these systems, heading estimation is achieved by monitoring the strength of the Earth’s magnetic field.
However, the Earth’s magnetic field can be locally distorted due to the proximity of ferrous and/or magnetic objects. Herein we propose a novel method for accurate 3D orientation estimation using an IMU, comprising of an accelerometer, gyroscope and magnetometer, under conditions of magnetic field distortion. The system performs online detection and compensation for magnetic disturbances, due to, for example, the presence of ferrous objects.
The magnetic distortions are detected by exploiting variations in magnetic dip angle, relative to the gravity vector, and in magnetic strength. We investigate and show the advantages of using both magnetic strength and magnetic dip angle for detecting the presence of magnetic distortions. The correction method is based on a particle filter, that performs correction using an adaptive cost function and by adapting the variance during particle resampling so as to place more emphasis on the results of dead reckoning the gyroscope measurements and less on the magnetometer readings. The proposed method was tested in an indoor environment in the presence of various magnetic distortions and under various accelerations (up to
3g). In the experiments, the proposed algorithm achieves < 2 ◦
Static Peak-to-Peak error and < 5 ◦ Dynamic Peak-to-Peak error, significantly outperforming previous methods.
Index Terms—AHRS, Particle filter, Data Fusion, Inertial
Measurement
Conditions of Magnetic Distortion
Nagesh Yadav∗, Chris Bleakley†
{nagesh.yadav∗, chris.bleakley†}@ucd.ie
UCD Complex and Adaptive Systems Laboratory, UCD School of Computer Science and Informatics,
University College Dublin, Ireland
Abstract—Low cost, compact Inertial Measurement Units
(IMUs) are now being used to track human body movements in indoor environments by estimation of the 3D orientation of body segments. In many of these systems, heading estimation is achieved by monitoring the strength of the Earth’s magnetic field.
However, the Earth’s magnetic field can be locally distorted due to the proximity of ferrous and/or magnetic objects. Herein we propose a novel method for accurate 3D orientation estimation using an IMU, comprising of an accelerometer, gyroscope and magnetometer, under conditions of magnetic field distortion. The system performs online detection and compensation for magnetic disturbances, due to, for example, the presence of ferrous objects.
The magnetic distortions are detected by exploiting variations in magnetic dip angle, relative to the gravity vector, and in magnetic strength. We investigate and show the advantages of using both magnetic strength and magnetic dip angle for detecting the presence of magnetic distortions. The correction method is based on a particle filter, that performs correction using an adaptive cost function and by adapting the variance during particle resampling so as to place more emphasis on the results of dead reckoning the gyroscope measurements and less on the magnetometer readings. The proposed method was tested in an indoor environment in the presence of various magnetic distortions and under various accelerations (up to
3g). In the experiments, the proposed algorithm achieves < 2 ◦
Static Peak-to-Peak error and < 5 ◦ Dynamic Peak-to-Peak error, significantly outperforming previous methods.
Index Terms—AHRS, Particle filter, Data Fusion, Inertial
Measurement