Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle
Joint Authors
Xing, Xiangwei
Zou, Huanxin
Ji, Kefeng
Sun, Jixiang
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-09
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently.
In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited.
The detailed procedure presented in this paper can be summarized as follows.
Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary.
Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle.
Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector.
Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.
American Psychological Association (APA)
Xing, Xiangwei& Ji, Kefeng& Zou, Huanxin& Sun, Jixiang. 2014. Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1051255
Modern Language Association (MLA)
Xing, Xiangwei…[et al.]. Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle. The Scientific World Journal No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1051255
American Medical Association (AMA)
Xing, Xiangwei& Ji, Kefeng& Zou, Huanxin& Sun, Jixiang. Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1051255
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051255