Article
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Preserved in Portico This version is not peer-reviewed
Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
Version 1
: Received: 21 November 2016 / Approved: 21 November 2016 / Online: 21 November 2016 (09:57:15 CET)
A peer-reviewed article of this Preprint also exists.
Shi, W.; Wang, Y.; Wu, Y. Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering. Sensors 2017, 17, 427, doi:10.3390/s17020427. Shi, W.; Wang, Y.; Wu, Y. Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering. Sensors 2017, 17, 427, doi:10.3390/s17020427.
Abstract
The foot-mounted inertial navigation system is an important application of pedestrian navigation as it in principle does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial sensors with ZUPT (zero-velocity update) and range decomposition constraint perform better than in either single way. This paper recommends that the distance of separation between the position estimates of feet-mounted inertial navigation systems be restricted in the ellipsoidal constraint which relates to the maximum step and leg height. The performance of the proposed method is studied utilizing experimental data. The results indicate that the method can effectively correct the dual navigation systems’ position over the existing spherical constraint.
Keywords
inertial navigation system; ZUPT; ellipsoidal constraint; correct position
Subject
Engineering, Control and Systems Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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