An Improved Particle Filter Algorithm for Geomagnetic Indoor Positioning

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dc.contributor.authorHuang, He
dc.contributor.authorLi, Wei
dc.contributor.authorLuo, De An
dc.contributor.authorQiu, Dong Wei
dc.contributor.authorGao, Yang
dc.date.accessioned2018-09-27T11:13:54Z
dc.date.available2018-09-27T11:13:54Z
dc.date.issued2018-03-19
dc.date.updated2018-09-27T11:13:54Z
dc.description.abstractGeomagnetic indoor positioning is an attractive indoor positioning technology due to its infrastructure-free feature. In the matching algorithm for geomagnetic indoor localization, the particle filter has been the most widely used. The algorithm however often suffers filtering divergence when there is continuous variation of the indoor magnetic distribution. The resampling step in the process of implementation would make the situation even worse, which directly lead to the loss of indoor positioning solution. Aiming at this problem, we have proposed an improved particle filter algorithm based on initial positioning error constraint, inspired by the Hausdorff distance measurement point set matching theory. Since the operating range of the particle filter cannot exceed the magnitude of the initial positioning error, it avoids the adverse effect of sampling particles with the same magnetic intensity but away from the target during the iteration process on the positioning system. The effectiveness and reliability of the improved algorithm are verified by experiments.
dc.description.versionPeer Reviewed
dc.identifier.citationHe Huang, Wei Li, De An Luo, Dong Wei Qiu, and Yang Gao, “An Improved Particle Filter Algorithm for Geomagnetic Indoor Positioning,” Journal of Sensors, vol. 2018, Article ID 5989678, 9 pages, 2018. doi:10.1155/2018/5989678
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/33001
dc.identifier.urihttp://dx.doi.org/10.1155/2018/5989678
dc.identifier.urihttp://hdl.handle.net/1880/108065
dc.language.rfc3066en
dc.rights.holderCopyright © 2018 He Huang et al. 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.
dc.titleAn Improved Particle Filter Algorithm for Geomagnetic Indoor Positioning
dc.typeJournal Article
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