A novel algorithm for tracking targets using manoeuvre models

• 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
• DOI: 10.1049/ic:20080066

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.