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Proceedings Paper

Model-based sensor fusion
Author(s): Leonid I. Perlovsky
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Paper Abstract

Fusion of information from multiple sources is an increasingly important area of research and application. This problem is often complicated by various sensors having different limitations and fields of view. Further complications result from the absence of prior knowledge. In addition to fusing diverse information, it is also necessary to manage multiple sensors with various limitations efficiently for optimal overall system performance. We have solved this set of problems using the MLANS neural network that employs model based approach and fuzzy decision logic.

Paper Details

Date Published: 1 November 1992
PDF: 4 pages
Proc. SPIE 1828, Sensor Fusion V, (1 November 1992); doi: 10.1117/12.131651
Show Author Affiliations
Leonid I. Perlovsky, Nichols Research Corp. (United States)

Published in SPIE Proceedings Vol. 1828:
Sensor Fusion V
Paul S. Schenker, Editor(s)

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