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Proceedings Paper

Fixed-lag sequential Monte Carlo data association
Author(s): Mark Briers; Arnaud Doucet; Simon R. Maskell; Paul R. Horridge
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Paper Abstract

The use of multiple scans of data to improve ones ability to improve target tracking performance is widespread in the tracking literature. In this paper, we introduce a novel application of a recent innovation in the SMC literature that uses multiple scans of data to improve the stochastic approximation (and so the data association ability) of a multiple target Sequential Monte Carlo based tracking system. Such an improvement is achieved by resimulating sampled variates over a fixed-lag time window by artificially extending the space of the target distribution. In doing so, the stochastic approximation is improved and so the data association ambiguity is more readily resolved.

Paper Details

Date Published: 19 May 2006
PDF: 12 pages
Proc. SPIE 6236, Signal and Data Processing of Small Targets 2006, 62360S (19 May 2006); doi: 10.1117/12.665684
Show Author Affiliations
Mark Briers, QinetiQ Ltd. (United Kingdom)
Cambridge Univ. (United Kingdom)
Arnaud Doucet, The Univ. of British Columbia (Canada)
Simon R. Maskell, QinetiQ Ltd. (United Kingdom)
Paul R. Horridge, QinetiQ Ltd. (United Kingdom)

Published in SPIE Proceedings Vol. 6236:
Signal and Data Processing of Small Targets 2006
Oliver E. Drummond, Editor(s)

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