Share Email Print
cover

Optical Engineering • Open Access

Neighborhood virtual points discriminant embedding for synthetic aperture radar automatic target recognition
Author(s): Jifang Pei; Yulin Huang; Xian Liu; Jianyu Yang

Paper Abstract

We propose a new feature extraction method for synthetic aperture radar automatic target recognition based on manifold learning theory. By introducing the virtual point in every sample’s neighborhood, we establish the spatial relationships of the neighborhoods. When the samples are embedded into the feature space, each sample moves toward its neighborhood virtual point, whereas the virtual points with the same class label get together, and the virtual points from different classes separate from each other. This can improve the classification and recognition performance effectively. Experiments based on the moving and stationary target acquisition and recognition database are conducted to verify the effectiveness of our method.

Paper Details

Date Published: 7 March 2013
PDF: 12 pages
Opt. Eng. 52(3) 036201 doi: 10.1117/1.OE.52.3.036201
Published in: Optical Engineering Volume 52, Issue 3
Show Author Affiliations
Jifang Pei, Univ. of Electronic Science and Technology of China (China)
Yulin Huang, Univ. of Electronic Science and Technology of China (China)
Xian Liu, Univ. of Electronic Science and Technology of China (China)
Jianyu Yang, Univ. of Electronic Science and Technology of China (China)


© SPIE. Terms of Use
Back to Top