Research of decision fusion for multi-source remote-sensing satellite information based on SVMs and DS evidence theory

Author

Chang, Zhuang ; Liao, Xuejun ; Liu, Yan ; Wang, Wei

Author_Institution

Dept. of Testing Command, Acad. of Equip. Command & Technol., Beijing, China

fYear

2011

fDate

19-21 Oct. 2011

Firstpage

416

Lastpage

420

Abstract

Satellite information is an important source of the decision-level intelligence in battlefield. Research of the multi-source information decision-level fusion provides a key technical approach for distilling comprehensive satellite information and acquiring decision-level intelligences. A SVMs-DS model adopting statistics theory and uncertainty reasoning method in the article, ensures precision and reliability for decision intelligence output, by establishing multi-class classifier of intelligent performance and conflict disposing mechanism of fine fault tolerance, which lays a practical foundation for multi-source remote-sensing satellite information decision-level fusion.

Keywords

decision making; inference mechanisms; military computing; pattern classification; remote sensing; sensor fusion; support vector machines; uncertainty handling; DS evidence theory; Dempster-Shafer theory; SVM; battlefield; decision fusion; decision-level intelligence; fault tolerance; information decision-level fusion; multiclass classifier; multisource remote-sensing satellite information; statistics theory; support vector machines; uncertainty reasoning method; Classification algorithms; Kernel; Remote sensing; Satellites; Support vector machines; Training; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-61284-374-2

Type

conf

DOI

10.1109/IWACI.2011.6160042

Filename

6160042