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Proceedings Paper

A survey of PHD filter and CPHD filter implementations
Author(s): Ronald Maher
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Paper Abstract

The probability hypothesis density (PHD) filter has attracted increasing interest since the author first introduced it in 2000. Potentially practical computational implementations of this filter have been devised, based on sequential Monte Carlo or on Gaussian mixture techniques. Research groups in at least a dozen different nations are investigating the PHD filter and its generalization, the CPHD filter, for use in various applications. Some of this work suggests that these filters may, under certain circumstances, outperform conventional multitarget filters such as MHT and JPDA. This paper summarizes these research efforts and their findings.

Paper Details

Date Published: 7 May 2007
PDF: 12 pages
Proc. SPIE 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI, 65670O (7 May 2007); doi: 10.1117/12.721125
Show Author Affiliations
Ronald Maher, Lockheed Martin MS2 Tactical Systems (United States)


Published in SPIE Proceedings Vol. 6567:
Signal Processing, Sensor Fusion, and Target Recognition XVI
Ivan Kadar, Editor(s)

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