Share Email Print
cover

Proceedings Paper

The multisensor PHD filter: I. General solution via multitarget calculus
Author(s): Ronald Mahler
Format Member Price Non-Member Price
PDF $14.40 $18.00

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. This paper introduces formulas for the actual "general multisensor intensity filter." In the companion paper I demonstrate that the "general multisensor intensity filter" will perform badly in even the easiest multitarget tracking problems; and argue that this suggests 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, 73360E (11 May 2009); doi: 10.1117/12.818024
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)

© SPIE. Terms of Use
Back to Top