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Proceedings Paper

User-defined information and scientific performance evaluation
Author(s): John R. Hoffman; Ronald P. S. Mahler; Tim Zajic
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Paper Abstract

For the past two years at this conference we have described results in the practical implementation of a unified, scientific approach to performance measurement for data fusion algorithms. Our approach is based on finite set statistics (FISST), a generalization of conventional statistics to multisource, multitarget problems. Finite-set statistics makes it possible to directly extend Shannon-type information metrics to multisource, multitarget problems in such a way that information can be defined and measured even though any given end-user may have conflicting or even subjective definitions of what information means. In this follow-on paper we describe the performance of FISST based metrics that take into account a user's definition of information and develop a rigorous theory of partial information for multisource, multi-target problems.

Paper Details

Date Published: 16 August 2001
PDF: 12 pages
Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); doi: 10.1117/12.436958
Show Author Affiliations
John R. Hoffman, Lockheed Martin Tactical Defence Systems (United States)
Ronald P. S. Mahler, Lockheed Martin Tactical Defence Systems (United States)
Tim Zajic, Lockheed Martin Tactical Defence Systems (United States)


Published in SPIE Proceedings Vol. 4380:
Signal Processing, Sensor Fusion, and Target Recognition X
Ivan Kadar, Editor(s)

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