Journal article icon

Journal article

Sensor fusion for magneto-inductive navigation

Abstract:
Magneto-inductive navigation is an inexpensive and easily deployable solution to many of today’s navigation problems. By utilizing very low frequency magnetic fields, magneto-inductive technology circumvents the problems with attenuation and multipath that often plague competing modalities. Using triaxial transmitter and receiver coils, it is possible to compute position and orientation estimates in three dimensions. However, in many situations, additional information is available that constrains the set of possible solutions. For example, the receiver may be known to be coplanar with the transmitter, or orientation information may be available from inertial sensors. We employ a maximum a posteriori estimator to fuse magneto-inductive signals with such complementary information. Further, we derive the Cramér-Rao bound for the position estimates and investigate the problem of detecting distortions caused by ferrous material. The performance of the estimator is compared to the Cramér-Rao bound and a state-of-the-art estimator using both simulations and real-world data. By fusing magneto-inductive signals with accelerometer measurements, the median position error is reduced almost by a factor of two.
Publication status:
Published
Peer review status:
Peer reviewed

Actions

Access Document

Files:
Publisher copy:
10.1109/jsen.2019.2942451

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Department:
Unknown
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:
Institute of Electrical and Electronics Engineers
Journal:
IEEE Sensors Journal More from this journal
Volume:
20
Issue:
1
Pages:
386 - 396
Publication date:
2019-09-19
Acceptance date:
2019-09-17
DOI:
EISSN:
1530-437X
ISSN:
2379-9153


Language:
English
Keywords:
Pubs id:
pubs:1055443
UUID:
uuid:6a760785-73f5-4906-be09-02fc12d55407
Local pid:
pubs:1055443
Source identifiers:
1055443
Deposit date:
2019-09-24
ARK identifier:

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP