Target Recognition in SAR Images Based on Multiresolution Representations with 2D Canonical Correlation Analysis
Joint Authors
Tan, Xiaojing
Zou, Ming
He, Xiqin
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-24
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This study proposes a synthetic aperture radar (SAR) target-recognition method based on the fused features from the multiresolution representations by 2D canonical correlation analysis (2DCCA).
The multiresolution representations were demonstrated to be more discriminative than the solely original image.
So, the joint classification of the multiresolution representations is beneficial to the enhancement of SAR target recognition performance.
2DCCA is capable of exploiting the inner correlations of the multiresolution representations while significantly reducing the redundancy.
Therefore, the fused features can effectively convey the discrimination capability of the multiresolution representations while relieving the storage and computational burdens caused by the original high dimension.
In the classification stage, the sparse representation-based classification (SRC) is employed to classify the fused features.
SRC is an effective and robust classifier, which has been extensively validated in the previous works.
The moving and stationary target acquisition and recognition (MSTAR) data set is employed to evaluate the proposed method.
According to the experimental results, the proposed method could achieve a high recognition rate of 97.63% for the 10 classes of targets under the standard operating condition (SOC).
Under the extended operating conditions (EOC) like configuration variance, depression angle variance, and the robustness of the proposed method are also quantitively validated.
In comparison with some other SAR target recognition methods, the superiority of the proposed method can be effectively demonstrated.
American Psychological Association (APA)
Tan, Xiaojing& Zou, Ming& He, Xiqin. 2020. Target Recognition in SAR Images Based on Multiresolution Representations with 2D Canonical Correlation Analysis. Scientific Programming،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1209110
Modern Language Association (MLA)
Tan, Xiaojing…[et al.]. Target Recognition in SAR Images Based on Multiresolution Representations with 2D Canonical Correlation Analysis. Scientific Programming No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1209110
American Medical Association (AMA)
Tan, Xiaojing& Zou, Ming& He, Xiqin. Target Recognition in SAR Images Based on Multiresolution Representations with 2D Canonical Correlation Analysis. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1209110
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209110