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Sensors 2018, 18(9), 2940; https://doi.org/10.3390/s18092940

Adaptive Local Aspect Dictionary Pair Learning for Synthetic Aperture Radar Target Image Classification

1
College of Communication Engineering, Chongqing University, Chongqing 400044, China
2
Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
3
Spacecraft General Design Department, China Academy of Space Technology, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Received: 3 June 2018 / Revised: 28 August 2018 / Accepted: 31 August 2018 / Published: 4 September 2018
(This article belongs to the Section Remote Sensors)
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Abstract

In this paper, a new target classification algorithm based on adaptive local aspect dictionary pair learning for synthetic aperture radar (SAR) images is developed. To that end, first, the aspect sector of one testing sample is determined adaptively by a regularized non-negative sparse learning method. Second, a synthesis dictionary and an analysis dictionary are jointly learned from the corresponding training subset located in the aspect sector. By doing so, the local aspect dictionary pair is obtained. Finally, the class label of the testing sample is inferred by a use of the minimum reconstruction residual under the representation with the local aspect dictionary pair. Using the local aspect sector training subset rather than the global aspect training set reduces the interference of a large amount of unrelated training samples, which leads to a more discriminative local aspect dictionary pair for target classification. The experiments are conducted with the Moving and Stationary Target Acquisition and Recognition (MSTAR) database, and the results demonstrate that the proposed approach is effective and superior to the state-of-the-art methods. View Full-Text
Keywords: SAR; images classification; dictionary learning; representation learning; aspect SAR; images classification; dictionary learning; representation learning; aspect
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Zhang, X.; Tan, Z.; Liu, G.; Liu, H.; Wang, Y.; Liu, S.; Li, Y.; Xu, H.; Xia, J. Adaptive Local Aspect Dictionary Pair Learning for Synthetic Aperture Radar Target Image Classification. Sensors 2018, 18, 2940.

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