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Target Recognition in SAR Images Based on Multiresolution Representations with 2D Canonical Correlation Analysis
المؤلفون المشاركون
Tan, Xiaojing
Zou, Ming
He, Xiqin
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-02-24
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1209110
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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