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Proceedings Paper

Extensions to adaptive Boolean decision fusion
Author(s): Martin E. Liggins
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Paper Abstract

The concepts of distributed decision fusion have shown considerable interest for many years, gaining its start with Tenney and Sandell in the early Eighties. Since then Bayesian detection fusion has shown a great deal of progress, adding considerable depth and flexibility to the decision process. It has also added a comparative degree of complexity to the evaluation process. This paper will address these complexities in terms of fusion performance. In addition, we will show that the CFAR process can be an effective means of fusion rule selection. The conditions under evaluation involve the use of three image change detection algorithms (two using SAR images, and one using Electro-Optical Imagery). Each change detection algorithm provides a unique observation of the environment. The Adaptive Boolean Decision Fusion (ABDF) process provides a basis for fusing and interpreting these change events.

Paper Details

Date Published: 31 July 2002
PDF: 9 pages
Proc. SPIE 4729, Signal Processing, Sensor Fusion, and Target Recognition XI, (31 July 2002); doi: 10.1117/12.477614
Show Author Affiliations
Martin E. Liggins, Veridian Systems, Inc. (United States)

Published in SPIE Proceedings Vol. 4729:
Signal Processing, Sensor Fusion, and Target Recognition XI
Ivan Kadar, Editor(s)

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