Target recognition of MMW radar based on FSVM

Author

Luan, Ying-hong ; Yue-hua ; Li, Yue-hua

Author_Institution

Inst. of Near Sensing Tech. with Millimeter Wave&Opt.-wave, Nanjing Univ. of Sci.&Tech., Nanjing

fYear

2008

fDate

3-5 June 2008

Firstpage

1417

Lastpage

1421

Abstract

The choice of fuzzy membership relates to the classification results of fuzzy support vector machine (FSVM). In this paper, membership based on distance and affinity among samples is researched. Aimed at the disadvantage of membership based on affinity among samples that can not reflect the distribution of radar echo in feature space, super-ellipse is introduced to improve the membership and applied to FSVM to distinguish support vectors with outliers or noise. The results of experiments show that the fuzzy support vector machine, based on the improved affinity among samples, is more robust than others.

Keywords

fuzzy set theory; radar target recognition; support vector machines; MMW radar; fuzzy support vector machine; membership decision; sample affinity; target recognition; Ellipsoids; Isolation technology; Machine learning; Millimeter wave radar; Millimeter wave technology; Pattern recognition; Spaceborne radar; Support vector machine classification; Support vector machines; Target recognition; FSVM; affinity; membership decision; target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-1717-9

Electronic_ISBN

978-1-4244-1718-6

Type

conf

DOI

10.1109/ICIEA.2008.4582752

Filename

4582752