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Remote Sensing
Volume 11
Issue 22
10.3390/rs11222676
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Article

SAR Target Recognition via Joint Sparse and Dense Representation of Monogenic Signal

by
Meiting Yu
*,
Sinong Quan
,
Gangyao Kuang
and
Shaojie Ni
College of Electronic Science, National University of Defense Technology, Changsha 410073, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(22), 2676; https://doi.org/10.3390/rs11222676
Submission received: 12 October 2019 / Revised: 12 November 2019 / Accepted: 12 November 2019 / Published: 15 November 2019
(This article belongs to the Section Remote Sensing Image Processing)
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Abstract

Synthetic aperture radar (SAR) target recognition under extended operating conditions (EOCs) is a challenging problem due to the complex application environment, especially for insufficient target variations and corrupted SAR images in the training samples. This paper proposes a new strategy to solve these problems for target recognition. The SAR images are firstly characterized by multi-scale components of monogenic signal. The generated monogenic features are decomposed to learn a class dictionary and a shared dictionary, which represent the possible intraclass variations information and the common information, respectively. Moreover, a sparse representation of the class dictionary and a dense representation of the shared dictionary are jointly employed to represent a query sample for classification. The validity of the proposed strategy is demonstrated with multiple comparative experiments on moving and stationary target acquisition and recognition (MSTAR) database.
Keywords: SAR; target recognition; monogenic signal; sparse representation; dense representation SAR; target recognition; monogenic signal; sparse representation; dense representation
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MDPI and ACS Style

Yu, M.; Quan, S.; Kuang, G.; Ni, S. SAR Target Recognition via Joint Sparse and Dense Representation of Monogenic Signal. Remote Sens. 2019, 11, 2676. https://doi.org/10.3390/rs11222676

AMA Style

Yu M, Quan S, Kuang G, Ni S. SAR Target Recognition via Joint Sparse and Dense Representation of Monogenic Signal. Remote Sensing. 2019; 11(22):2676. https://doi.org/10.3390/rs11222676

Chicago/Turabian Style

Yu, Meiting, Sinong Quan, Gangyao Kuang, and Shaojie Ni. 2019. "SAR Target Recognition via Joint Sparse and Dense Representation of Monogenic Signal" Remote Sensing 11, no. 22: 2676. https://doi.org/10.3390/rs11222676

APA Style

Yu, M., Quan, S., Kuang, G., & Ni, S. (2019). SAR Target Recognition via Joint Sparse and Dense Representation of Monogenic Signal. Remote Sensing, 11(22), 2676. https://doi.org/10.3390/rs11222676

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