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
Language English
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MeetingName IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications, 15-16 April 2008, Birmingham, UK
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PublicationTitle IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications
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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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StartPage 141
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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