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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| Veröffentlicht in: | IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications S. 141 - 148 |
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| Hauptverfasser: | , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
Stevenage
IET
2008
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| Schlagworte: | |
| ISBN: | 0863419100, 9780863419102 |
| Online-Zugang: | Volltext |
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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. |
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| 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 |
| Author_xml | – sequence: 1 givenname: K surname: Gilholm fullname: Gilholm, K organization: QinetiQ, Farnborough – sequence: 2 givenname: N.O surname: Everett fullname: 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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| 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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