Hypothesis management for information fusion

Author

Jones, Eric K. ; Denis, Nikolaos ; Hunter, Daniel

Author_Institution

Alphatech Inc., Burlington, MA, USA

Volume

18

Issue

6

fYear

2003

fDate

6/1/2003 12:00:00 AM

Firstpage

3

Lastpage

8

Abstract

The efficient management of large collections of fusion hypotheses presents a critical challenge for scaling high-level information fusion systems to solve large problems. We motivate this challenge in the context of two Alphatech research projects, and discuss several partial solutions. A recurring theme is the exploitation of space-efficient, factored representations of multiple hypotheses to enable an efficient search for good hypotheses.

Keywords

associative processing; data structures; heuristic programming; inference mechanisms; information analysis; information theory; abductive reasoning technology; data associations; high-level information fusion system scaling; information fusion hypothesis management; large fusion hypotheses collections; large problem solution; observable data; observation inference techniques; space-efficient factored representations; system structure/behavior/intent; Information management; Kinematics; Knowledge management; Mathematical model; Missiles; Programming profession; Road vehicles; State estimation; Time factors; Vehicle driving;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems Magazine, IEEE

Publisher

ieee

ISSN

0885-8985

Type

jour

DOI

10.1109/MAES.2003.1209583

Filename

1209583