Bayesian Fusion of Asynchronous Inertial, Speed and Position Data for Object Tracking
Accepted version
Peer-reviewed
Repository URI
Repository DOI
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Authors
Liang, Jiaming https://orcid.org/0000-0002-1318-4481
Godsill, S
Abstract
In this paper we present Bayesian methods for tracking scenarios in which an intrinsic coordinate model is considered and inertial mea- surements plus occasional position fixes are available. The methods are first tested using synthetic data, giving a comprehensive evalu- ation as to their performance. Further evaluation on real data also reveals our approaches can be favourable alternatives to existing in- ertial tracking/navigation models.
Description
Keywords
46 Information and Computing Sciences, 40 Engineering, 4001 Aerospace Engineering
Journal Title
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Conference Name
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Journal ISSN
1520-6149
Volume Title
2019-May
Publisher
IEEE
Publisher DOI
Rights
All rights reserved