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Proceedings Paper

Poisson models for extended target and group tracking
Author(s): Kevin Gilholm; Simon Godsill; Simon Maskell; David Salmond
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Paper Abstract

It is common practice to represent a target group (or an extended target) as set of point sources and attempt to formulate a tracking filter by constructing possible assignments between measurements and the sources. We suggest an alternative approach that produces a measurement model (likelihood) in terms of the spatial density of measurements over the sensor observation region. In particular, the measurements are modelled as a Poisson process with a spatially dependent rate parameter. This representation allows us to model extended targets as an intensity distribution rather than a set of points and, for a target formation, it gives the option of modelling part of the group as a spatial distribution of target density. Furthermore, as a direct consequence of the Poisson model, the measurement likelihood may be evaluated without constructing explicit association hypotheses. This considerably simplifies the filter and gives a substantial computational saving in a particle filter implementation. The Poisson target-measurement model will be described and its relationship to other filters will be discussed. Illustrative simulation examples will be presented.

Paper Details

Date Published: 15 September 2005
PDF: 12 pages
Proc. SPIE 5913, Signal and Data Processing of Small Targets 2005, 59130R (15 September 2005); doi: 10.1117/12.618730
Show Author Affiliations
Kevin Gilholm, QinetiQ, Ltd. (United Kingdom)
Simon Godsill, Univ. of Cambridge (United Kingdom)
Simon Maskell, QinetiQ, Ltd. (United Kingdom)
David Salmond, QinetiQ, Ltd. (United Kingdom)


Published in SPIE Proceedings Vol. 5913:
Signal and Data Processing of Small Targets 2005
Oliver E. Drummond, Editor(s)

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