A Review of Data Fusion Techniques

被引：523
作者：
Castanedo, Federico [1 ]
机构：
[1] Univ Deusto, DeustoTech, Deusto Inst Technol, Bilbao 48007, Spain
来源：
SCIENTIFIC WORLD JOURNAL | 2013年
关键词：
DATA ASSOCIATION; TRACKING; ALGORITHM; DEMPSTER; ARCHITECTURES; EXPLOITATION; MODELS;
D O I：
10.1155/2013/704504
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
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.
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页数：19
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