A complementary observer-based approach for the estimation of motion in rigid bodies using inertial and magnetic sensors

This paper addresses the problem of rigid body orientation tracking. A complementary nonlinear observer is proposed for attitude estimation using inertial/magnetic sensors. The approach developed here is applied in Bio-logging, an interdisciplinary research area at the intersection of animal behavior and bioengineering. We propose a state estimation algorithm that combines three complementary data obtained from a 3-axis accelerometer, a 3-axis magnetometer and a 3-axis gyroscope in order to provide the best attitude. The proposed algorithm is based on a nonlinear observer coupled with an Iterated Least Squares Algorithm (ISLA). The evaluation of the state estimator by simulation is followed by some experiments illustrating the efficiency of the proposed approach.