A novel algorithm for tracking targets using manoeuvre models

We present a novel algorithm for robust tracking of targets in challenging scenarios by modelling their high level behaviour. The particle-filter [6] based algorithm combines the benefits of variable-rate filtering [5] with a variable- dimension, manoeuvre-based representation of the target trajecto...

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Published in:	IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications pp. 141 - 148
Main Authors:	Gilholm, K, Everett, N.O
Format:	Conference Proceeding
Language:	English
Published:	Stevenage IET 2008
Subjects:	Filtering methods in signal processing Markov processes Monte Carlo methods Signal processing theory reversible-jump Markov Chain Monte Carlo resample-move fashion Monte Carlo methods manoeuvre models variable-rate filtering target trajectory target tracking robust target tracking Markov processes particle filtering (numerical methods) particle-filter based algorithm
ISBN:	0863419100, 9780863419102
Online Access:	Get full text
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Abstract	We present a novel algorithm for robust tracking of targets in challenging scenarios by modelling their high level behaviour. The particle-filter [6] based algorithm combines the benefits of variable-rate filtering [5] with a variable- dimension, manoeuvre-based representation of the target trajectory. Variable-rate filtering allows the algorithm to model manoeuvre changes at arbitrary (non-measurement) times, while manoeuvre-based modelling adds to track robustness by providing a parsimonious representation of the target trajectory. The efficiency of the particle filter has been greatly enhanced using reversible-jump Markov Chain Monte Carlo [7] moves that are applied in a Resample-Move fashion [4]. We demonstrate the performance of the algorithm on some example representative scenarios.
AbstractList	We present a novel algorithm for robust tracking of targets in challenging scenarios by modelling their high level behaviour. The particle-filter [6] based algorithm combines the benefits of variable-rate filtering [5] with a variable- dimension, manoeuvre-based representation of the target trajectory. Variable-rate filtering allows the algorithm to model manoeuvre changes at arbitrary (non-measurement) times, while manoeuvre-based modelling adds to track robustness by providing a parsimonious representation of the target trajectory. The efficiency of the particle filter has been greatly enhanced using reversible-jump Markov Chain Monte Carlo [7] moves that are applied in a Resample-Move fashion [4]. We demonstrate the performance of the algorithm on some example representative scenarios.
Author	Gilholm, K Everett, N.O
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Keywords	reversible-jump Markov Chain Monte Carlo resample-move fashion Monte Carlo methods manoeuvre models variable-rate filtering target trajectory target tracking robust target tracking Markov processes particle filtering (numerical methods) particle-filter based algorithm
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Snippet	We present a novel algorithm for robust tracking of targets in challenging scenarios by modelling their high level behaviour. The particle-filter [6] based...
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SubjectTerms	Filtering methods in signal processing Markov processes Monte Carlo methods Signal processing theory
Title	A novel algorithm for tracking targets using manoeuvre models
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