Product Dictionary Learning-Based SAR Target Configuration Recognition

Dictionary construction is a key factor for the sparse representation- (SR-) based algorithms. It has been verified that the learned dictionaries are more effective than the predefined ones. In this paper, we propose a product dictionary learning (PDL) algorithm to achieve synthetic aperture radar (...

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Main Authors: Ming Liu, Shichao Chen, Fugang Lu, Junsheng Liu
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2020/9704829
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author Ming Liu
Shichao Chen
Fugang Lu
Junsheng Liu
author_facet Ming Liu
Shichao Chen
Fugang Lu
Junsheng Liu
author_sort Ming Liu
collection DOAJ
description Dictionary construction is a key factor for the sparse representation- (SR-) based algorithms. It has been verified that the learned dictionaries are more effective than the predefined ones. In this paper, we propose a product dictionary learning (PDL) algorithm to achieve synthetic aperture radar (SAR) target configuration recognition. The proposed algorithm obtains the dictionaries from a statistical standpoint to enhance the robustness of the proposed algorithm to noise. And, taking the inevitable multiplicative speckle in SAR images into account, the proposed algorithm employs the product model to describe SAR images. A more accurate description of the SAR image results in higher recognition rates. The accuracy and robustness of the proposed algorithm are validated by the moving and stationary target acquisition and recognition (MSTAR) database.
format Article
id doaj-art-8c1fb6ca40b9443d87c4e1fa6c0ee682
institution Kabale University
issn 1687-5869
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language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series International Journal of Antennas and Propagation
spelling doaj-art-8c1fb6ca40b9443d87c4e1fa6c0ee6822025-08-20T03:37:41ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772020-01-01202010.1155/2020/97048299704829Product Dictionary Learning-Based SAR Target Configuration RecognitionMing Liu0Shichao Chen1Fugang Lu2Junsheng Liu3Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an 710062, ChinaNo. 203 Research Institute of China Ordnance Industries, Xi’an 710065, ChinaNo. 203 Research Institute of China Ordnance Industries, Xi’an 710065, ChinaNo. 203 Research Institute of China Ordnance Industries, Xi’an 710065, ChinaDictionary construction is a key factor for the sparse representation- (SR-) based algorithms. It has been verified that the learned dictionaries are more effective than the predefined ones. In this paper, we propose a product dictionary learning (PDL) algorithm to achieve synthetic aperture radar (SAR) target configuration recognition. The proposed algorithm obtains the dictionaries from a statistical standpoint to enhance the robustness of the proposed algorithm to noise. And, taking the inevitable multiplicative speckle in SAR images into account, the proposed algorithm employs the product model to describe SAR images. A more accurate description of the SAR image results in higher recognition rates. The accuracy and robustness of the proposed algorithm are validated by the moving and stationary target acquisition and recognition (MSTAR) database.http://dx.doi.org/10.1155/2020/9704829
spellingShingle Ming Liu
Shichao Chen
Fugang Lu
Junsheng Liu
Product Dictionary Learning-Based SAR Target Configuration Recognition
International Journal of Antennas and Propagation
title Product Dictionary Learning-Based SAR Target Configuration Recognition
title_full Product Dictionary Learning-Based SAR Target Configuration Recognition
title_fullStr Product Dictionary Learning-Based SAR Target Configuration Recognition
title_full_unstemmed Product Dictionary Learning-Based SAR Target Configuration Recognition
title_short Product Dictionary Learning-Based SAR Target Configuration Recognition
title_sort product dictionary learning based sar target configuration recognition
url http://dx.doi.org/10.1155/2020/9704829
work_keys_str_mv AT mingliu productdictionarylearningbasedsartargetconfigurationrecognition
AT shichaochen productdictionarylearningbasedsartargetconfigurationrecognition
AT fuganglu productdictionarylearningbasedsartargetconfigurationrecognition
AT junshengliu productdictionarylearningbasedsartargetconfigurationrecognition