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Proceedings Paper

CPHD and PHD filters for unknown backgrounds, part III: tractable multitarget filtering in dynamic clutter
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Paper Abstract

In a previous conference paper the first author addressed the problem of devising CPHD and PHD filters that are capable of multitarget detection and tracking in unknown, dynamically changing clutter. That paper assumed that the clutter process is Poisson with an intensity function that is a finite mixture with unknown parameters. The measurement-update equations for these CPHD/PHD filters involved combinatorial sums over all partitions of the current measurement-set. This paper describes an approach that avoids combinatorial sums and is therefore potentially computationally tractable. Clutter is assumed to be a binomial i.i.d. cluster process with unknown parameters. Given this, three different and successively more tractable CPHD/PHD filters are derived, all capable of multitarget track-before-detect capability. The first assumes that the entire intensity function of the clutter process is unknown. The second and third assume that the clutter spatial distribution is known but that the clutter rate (number of clutter returns per scan) is unknown.

Paper Details

Date Published: 15 April 2010
PDF: 12 pages
Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 76980F (15 April 2010); doi: 10.1117/12.849470
Show Author Affiliations
Ronald Mahler, Lockheed Martin MS2 (United States)
Adel El-Fallah, Scientific Systems Co., Inc. (United States)

Published in SPIE Proceedings Vol. 7698:
Signal and Data Processing of Small Targets 2010
Oliver E. Drummond, Editor(s)

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