NDLI: Efficient particle filtering for road-constrained target tracking

Content Provider	IEEE Xplore Digital Library
Author	Cheng, Y. Singh, T.
Copyright Year	2005
Description	Author affiliation: Dept. of Mech. & Aerosp. Eng., State Univ. of New York, Amherst, NY, USA (Cheng, Y.; Singh, T.)
Abstract	The variable-structure multiple model particle filtering approach for state estimation of road-constrained targets is addressed. The multiple models are designed to account for target maneuvers including "move-stop-move" and motion ambiguity at an intersection; the time-varying active model sets are adaptively selected based on target state and local terrain condition. The hybrid state space is partitioned into the mode subspace and the target subspace. The mode state is estimated based on random sampling; the target state as well as the relevant likelihood function associated with a mode sample sequence is approximated as Gaussian distribution, of which the conditional mean and covariance are deterministically computed using nonlinear Kalman filtering. The importance function for the sampling of the mode state approximates the optimal importance function under the same Gaussian assumption of the target state.
File Size	2221850
File Format	PDF
ISBN	0780392868
DOI	10.1109/ICIF.2005.1591850
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filtering Target tracking State estimation Particle filters Motion estimation Sampling methods Roads Uncertainty Aerospace engineering State-space methods
Content Type	Text
Resource Type	Article

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