Skewed-redundant Hall-effect Magnetic Sensor Fusion for
Perturbation-free Indoor Heading Estimation
Abstract
Robust attitude and heading estimation with respect to a known reference
is an essential component for indoor localization in robotic
applications. Affordable Attitude and Heading Reference Systems (AHRS)
are typically using 9-axis solid-state MEMS-based sensors. The accuracy
of heading estimation on such a system depends on the Earth’s magnetic
field measurement accuracy. The measurement of the Earth’s magnetic
field using MEMS-based magnetometer sensors in an indoor environment,
however, is strongly affected by external magnetic perturbations. This
paper presents a novel approach for robust indoor heading estimation
based on skewed-redundant magnetometer fusion. A tetrahedron platform
based on Hall-effect magnetic sensors is designed to determine the
Earth’s magnetic field with the ability to compensate for external
magnetic field anomalies. Additionally, a correlation-based fusion
technique is introduced for perturbation mitigation using the proposed
skewed-redundant configuration. The proposed fusion technique uses a
correlation coefficient analysis for determining the distorted axis and
extracts the perturbation-free Earth’s magnetic field vector from the
redundant magnetic measurement. Our experimental results show that the
proposed scheme is able to successfully mitigate the anomalies in the
magnetic field measurement and estimates the Earth’s true magnetic
field. Using the proposed platform, we achieve a Root Mean Square Error
of 12.74$\degree$ for indoor heading estimation without
using an additional gyroscope.