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The Scientific World Journal
Volume 2013, Article ID 704504, 19 pages
http://dx.doi.org/10.1155/2013/704504
Review Article

A Review of Data Fusion Techniques

Deusto Institute of Technology, DeustoTech, University of Deusto, Avenida de las Universidades 24, 48007 Bilbao, Spain

Received 9 August 2013; Accepted 11 September 2013

Academic Editors: Y. Takama and D. Ursino

Copyright © 2013 Federico Castanedo. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The integration of data and knowledge from several sources is known as data fusion. This paper summarizes the state of the data fusion field and describes the most relevant studies. We first enumerate and explain different classification schemes for data fusion. Then, the most common algorithms are reviewed. These methods and algorithms are presented using three different categories: (i) data association, (ii) state estimation, and (iii) decision fusion.