Quaternion Based Heading Estimation with Handheld MEMS in Indoor Environments

V. Renaudin, C. Combettes, F. Peyret

Abstract: Pedestrian Dead-Reckoning (PDR) is the prime candidate for autonomous navigation with self-contained sensors. Nevertheless with noisy sensor signals and high hand dynamics, estimating accurate attitude angles remains a challenge for achieving long term positioning accuracy. A new attitude estimation algorithm based on a quaternion parameterization directly in the state vector and two opportunistic updates, i.e. magnetic angular rate update and acceleration gradient update, is proposed. The benefit of this method is assessed both at the theoretical level and at the experimental level. The error on the heading, estimated only with the PDR navigation algorithms, is found to less than 7° after 1 km of walk.
Published in: Proceedings of IEEE/ION PLANS 2014
May 5 - 8, 2014
Hyatt Regency Hotel
Monterey, CA
Pages: 645 - 656
Cite this article: Renaudin, V., Combettes, C., Peyret, F., "Quaternion Based Heading Estimation with Handheld MEMS in Indoor Environments," Proceedings of IEEE/ION PLANS 2014, Monterey, CA, May 2014, pp. 645-656.
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