Evaluation of AHRS algorithms for inertial personal localization in industrial environments

Abstract

This paper presents a comparison among several state-of-the-art Attitude and Heading Reference Systems (AHRS). These algorithms can be used for 3D orientation and position estimation of users or devices. The robust performance of these AHRS algorithms is of paramount importance, specially in environments with potential external perturbations, such as industrial environments. The comparison among AHRS algorithms presented in this paper also includes an algorithm recently proposed by the authors (DLR-AHRS). In this paper the performance of the different AHRS will be studied, including the effect of magnetic perturbations on the performance of orientation estimation, and the effect of using different patterns of motion when the sensor is carried by a user at different locations (pocket, foot/shoe, hand). These AHRS algorithms are also compared with the Kalman-based commercially available AHRS algorithm of Xsens. The performance of the AHRS algorithms depends strongly on the strategies used to reject perturbations (sudden accelerations or deformations of the Earth magnetic field) and the ability of the systems to estimate the biases of the gyroscopes.