dc.contributor.author | Wahlstrom, J | |
dc.contributor.author | Skog, I | |
dc.contributor.author | Gustafsson, F | |
dc.contributor.author | Markham, A | |
dc.contributor.author | Trigoni, N | |
dc.date.accessioned | 2020-07-22T14:16:43Z | |
dc.date.issued | 2019-05-15 | |
dc.description.abstract | A Bayesian zero-velocity detector for foot-mounted inertial navigation systems is presented. The detector
extends existing zero-velocity detectors based on the likelihood-ratio test and allows, possibly time-dependent, prior
information about the two hypotheses—the sensors being stationary or in motion—to be incorporated into the test. It is
also possible to incorporate information about the cost of a missed detection or a false alarm. Specifically, we consider
a hypothesis prior based on the velocity estimates provided by the navigation system and an exponential model for how
the cost of a missed detection increases with the time since the last zero-velocity update. Thereby, we obtain a detection
threshold that adapts to the motion characteristics of the user. Thus, the proposed detection framework efficiently solves
one of the key challenges in current zero-velocity-aided inertial navigation systems: the tuning of the zero-velocity detection
threshold. A performance evaluation on data with normal and fast gait demonstrates that the proposed detection framework
outperforms any detector that chooses two separate fixed thresholds for the two gait speeds. | en_GB |
dc.identifier.citation | Vol. 3, 7000704 | en_GB |
dc.identifier.doi | 10.1109/lsens.2019.2917055 | |
dc.identifier.uri | http://hdl.handle.net/10871/122082 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.rights | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be
obtained for all other uses, in any current or future media, including
reprinting/republishing this material for advertising or promotional purposes, creating new
collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted
component of this work in other works. | en_GB |
dc.subject | Sensor signals processing | en_GB |
dc.subject | sensor applications | en_GB |
dc.subject | adaptive thresholding | en_GB |
dc.subject | foot-mounted inertial navigation | en_GB |
dc.subject | indoor localization | en_GB |
dc.subject | posterior odds ratio | en_GB |
dc.subject | zero-velocity updates | en_GB |
dc.title | Zero-velocity detection—a Bayesian approach to adaptive thresholding | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-07-22T14:16:43Z | |
dc.description | This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record | en_GB |
dc.identifier.journal | IEEE Sensors Letters | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
dcterms.dateAccepted | 2019-05-13 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-05-15 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-07-22T14:13:40Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-07-22T14:16:50Z | |
refterms.panel | B | en_GB |