A Trident Quaternion Framework for Inertial-based Navigation Part II: Error Models and Application to Initial Alignment

TL;DR

This paper develops error models for a quaternion-based inertial navigation framework, designs EKFs based on these models, and demonstrates improved convergence and robustness in static and in-motion land vehicle alignment through simulations and field tests.

Contribution

It introduces new error models for the trident quaternion framework and applies them to design EKFs with enhanced convergence properties for land vehicle navigation.

Findings

L/RQEKF converge faster in static alignment than traditional EKF.

L/RQEKF have larger convergence regions in in-motion alignment.

High estimation consistency observed in simulations and field tests.

Abstract

This work deals with error models for trident quaternion framework proposed in the companion paper (Part I) and further uses them to investigate the odometer-aided static/in-motion inertial navigation attitude alignment for land vehicles. By linearizing the trident quaternion kinematic equation, the left and right trident quaternion error models are obtained, which are found to be equivalent to those derived from profound group affine. The two error models are used to design their corresponding extended Kalman filters (EKF), namely, the left-quaternion EKF (LQEKF) and the right-quaternion EKF (RQEKF). Simulations and field tests are conducted to evaluate their actual performances. Owing to the high estimation consistency, the L/RQEKF converge much faster in the static alignment than the traditional error model-based EKF, even under arbitrary large heading initialization. For the in-motion alignment, the L/RQEKF possess much larger convergence region than the traditional EKF does, although they still require the aid of attitude initialization so as to avoid large initial attitude errors.