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Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering

The foot-mounted inertial navigation system is an important method 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 syst...

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Detalles Bibliográficos
Autores principales: Shi, Wei, Wang, Yang, Wu, Yuanxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335982/
https://www.ncbi.nlm.nih.gov/pubmed/28241448
http://dx.doi.org/10.3390/s17020427
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author Shi, Wei
Wang, Yang
Wu, Yuanxin
author_facet Shi, Wei
Wang, Yang
Wu, Yuanxin
author_sort Shi, Wei
collection PubMed
description The foot-mounted inertial navigation system is an important method 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 pedestrian navigation aided with both ZUPT (zero velocity update) and the range decomposition constraint performs better than those in their own respective methods. This paper recommends that the separation distance between the position estimates of the two foot-mounted inertial navigation systems be restricted by an ellipsoidal constraint that relates to the maximum step length and the leg height. The performance of the proposed method is studied by utilizing experimental data, and the results indicate that the method can effectively correct the dual navigation systems’ position over the traditional spherical constraint.
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spelling pubmed-53359822017-03-16 Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering Shi, Wei Wang, Yang Wu, Yuanxin Sensors (Basel) Article The foot-mounted inertial navigation system is an important method 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 pedestrian navigation aided with both ZUPT (zero velocity update) and the range decomposition constraint performs better than those in their own respective methods. This paper recommends that the separation distance between the position estimates of the two foot-mounted inertial navigation systems be restricted by an ellipsoidal constraint that relates to the maximum step length and the leg height. The performance of the proposed method is studied by utilizing experimental data, and the results indicate that the method can effectively correct the dual navigation systems’ position over the traditional spherical constraint. MDPI 2017-02-22 /pmc/articles/PMC5335982/ /pubmed/28241448 http://dx.doi.org/10.3390/s17020427 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shi, Wei
Wang, Yang
Wu, Yuanxin
Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
title Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
title_full Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
title_fullStr Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
title_full_unstemmed Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
title_short Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
title_sort dual mimu pedestrian navigation by inequality constraint kalman filtering
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335982/
https://www.ncbi.nlm.nih.gov/pubmed/28241448
http://dx.doi.org/10.3390/s17020427
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AT wuyuanxin dualmimupedestriannavigationbyinequalityconstraintkalmanfiltering