An Observability-Constrained Magnetic Field-Aided Inertial Navigation System -- Extended Version

TL;DR

This paper introduces an observability-constrained magnetic field-aided inertial navigation system that improves yaw estimation consistency and accuracy by extending existing EKF methods, validated through simulation and real-world data.

Contribution

It extends the observability-constrained EKF to magnetic field-based odometry, enhancing yaw observability and uncertainty consistency in inertial navigation systems.

Findings

Preserves system observability properties.

Increases estimation accuracy.

Improves consistency of perceived uncertainty.

Abstract

Maintaining consistent uncertainty estimates in localization systems is crucial as the perceived uncertainty commonly affects high-level system components, such as control or decision processes. A method for constructing an observability-constrained magnetic field-aided inertial navigation system is proposed to address the issue of erroneous yaw observability, which leads to inconsistent estimates of yaw uncertainty. The proposed method builds upon the previously proposed observability-constrained extended Kalman filter and extends it to work with a magnetic field-based odometry-aided inertial navigation system. The proposed method is evaluated using simulation and real-world data, showing that (i) the system observability properties are preserved, (ii) the estimation accuracy increases, and (iii) the perceived uncertainty calculated by the EKF is more consistent with the true uncertainty of the filter estimates.