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Proceedings Paper

The multisensor PHD filter: II. Erroneous solution via Poisson magic
Author(s): Ronald Mahler
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Paper Abstract

The theoretical foundation for the probability hypothesis density (PHD) filter is the FISST multitarget differential and integral calculus. The "core" PHD filter presumes a single sensor. Theoretically rigorous formulas for the multisensor PHD filter can be derived using the FISST calculus, but are computationally intractable. A less theoretically desirable solution-the iterated-corrector approximation-must be used instead. Recently, it has been argued that an "elementary" methodology, the "Poisson-intensity approach," renders FISST obsolete. It has further been claimed that the iterated-corrector approximation is suspect, and in its place an allegedly superior "general multisensor intensity filter" has been proposed. In this and a companion paper I demonstrate that it is these claims which are erroneous. The companion paper introduces formulas for the actual "general multisensor intensity filter." In this paper I demonstrate that (1) the "general multisensor intensity filter" fails in important special cases; (2) it will perform badly in even the easiest multitarget tracking problems; and (3) these rather serious missteps suggest that the "Poisson-intensity approach" is inherently faulty.

Paper Details

Date Published: 11 May 2009
PDF: 12 pages
Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 73360D (11 May 2009); doi: 10.1117/12.818025
Show Author Affiliations
Ronald Mahler, Lockheed Martin MS2 Tactical Systems (United States)


Published in SPIE Proceedings Vol. 7336:
Signal Processing, Sensor Fusion, and Target Recognition XVIII
Ivan Kadar, Editor(s)

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