Online Particle Smoothing with Application to Map-Matching
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Publication Date
2022Journal Title
IEEE Transactions on Signal Processing
ISSN
1053-587X
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Duffield, S., & Singh, S. (2022). Online Particle Smoothing with Application to Map-Matching. IEEE Transactions on Signal Processing https://doi.org/10.1109/TSP.2022.3141259
Abstract
We introduce a novel method for online smoothing in state-space models that utilises a fixed-lag approximation to overcome the well known issue of path degeneracy.
Unlike classical fixed-lag techniques that only approximate certain marginals, we introduce an online resampling algorithm, called particle stitching, that converts these marginal samples into a full posterior approximation.
We demonstrate the utility of our method in the context of map-matching, the task of inferring a vehicle's trajectory given a road network and noisy GPS observations. We develop a new state-space model for the difficult task of map-matching on dense, urban road networks.
Sponsorship
EPSRC (1890282)
Engineering and Physical Sciences Research Council (1890282)
Identifiers
External DOI: https://doi.org/10.1109/TSP.2022.3141259
This record's URL: https://www.repository.cam.ac.uk/handle/1810/332125
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