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Journal article

Underground incrementally deployed magneto-inductive 3-D positioning network

Abstract:
Underground mines are characterized by a network of intersecting tunnels and sharp turns, an environment which is particularly challenging for radiofrequency based positioning systems due to extreme multipath, non-line-of-sight propagation, and poor anchor geometry. Such systems typically require a dense grid of devices to enable 3-D positioning. Moreover, the precise position of each anchor node needs to be precisely surveyed, a particularly challenging task in underground environments. Magneto-inductive (MI) positioning, which provides 3-D position and orientation from a single transmitter and penetrates thick layers of soil and rock without loss, is a more promising approach, but so far has only been investigated in simple point-to-point contexts. In this paper, we develop a novel MI positioning approach to cover an extended underground 3-D space with unknown geometry using a rapidly deployable anchor network. The key to our approach is that the position of only a single anchor needs to be accurately surveyed-the positions of all secondary anchors are determined using an iterative refinement process using measurements obtained from receivers within the network. This avoids the particularly challenging and time-intensive task in an underground environment of accurately surveying the positions of all of the transmitters. We also demonstrate how measurements obtained from multiple transmitters can be fused to improve localization accuracy. We validate the proposed approach in a man-made cave and show that, with a portable system that took 5 min to deploy, we were able to provide accurate through-the-earth location capability to nodes placed along a suite of tunnels.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/tgrs.2016.2540722

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author


Publisher:
IEEE
Journal:
IEEE Transactions on Geoscience and Remote Sensing More from this journal
Volume:
54
Issue:
8
Pages:
4376 - 4391
Publication date:
2016-04-12
Acceptance date:
2016-02-06
DOI:
EISSN:
1558-0644
ISSN:
0196-2892


Language:
English
Keywords:
Pubs id:
pubs:600066
UUID:
uuid:5d39c0a9-31ad-4de4-808a-b84900125b91
Local pid:
pubs:600066
Source identifiers:
600066
Deposit date:
2016-02-10

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