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Proceedings Paper

Methods of approximate agreement for multisensor fusion
Author(s): Richard Ree Brooks; S. Sitharama Iyengar
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Paper Abstract

Multisensor fusion is a method for improving sensor reliability. Because individual sensors are prone to errors and noise, it is advisable to fuse readings from many sensors. This allows several technologies to be used to measure the value of a variable. Unfortunately it is a non- trivial task to glean the best interpretation from a large number of partially contradictory sensor readings. A number of methods exist for finding the best approximate match for this type of redundant, but possibly faulty, data. This paper states the approximate matching problem and its application to multisensor fusion. Existing algorithms and recent developments are explained along with their performance and assumptions. A new algorithm is presented which unifies previous research. Appropriate applications and potential bottlenecks are discussed.

Paper Details

Date Published: 5 July 1995
PDF: 8 pages
Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213053
Show Author Affiliations
Richard Ree Brooks, Louisiana State Univ. (United States)
S. Sitharama Iyengar, Louisiana State Univ. (United States)


Published in SPIE Proceedings Vol. 2484:
Signal Processing, Sensor Fusion, and Target Recognition IV
Ivan Kadar; Vibeke Libby, Editor(s)

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