Online Particle Smoothing with Application to Map-Matching


Type
Article
Change log
Authors
Singh, S 
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.

Description
Keywords
Smoothing methods, Approximation algorithms, State-space methods, Additives, Trajectory, Signal processing algorithms, Task analysis, State-space models, sequential Monte Carlo, particle smoothing, backward simulation, map-matching, GPS
Journal Title
IEEE Transactions on Signal Processing
Conference Name
Journal ISSN
1053-587X
1941-0476
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Sponsorship
EPSRC (1890282)
Engineering and Physical Sciences Research Council (1890282)