JACIII Vol.23 No.3 pp. 414-420
doi: 10.20965/jaciii.2019.p0414


SAR Target Recognition via Joint Classification of Monogenic Components with Discrimination Analysis

Zhenyu Zhang

School of Automation and Electrical Engineering, Zhejiang University of Science and Technology
No.318 Liuhe Road, Hangzhou, Zhejiang 310023, China

April 24, 2018
October 12, 2018
May 20, 2019
synthetic aperture radar (SAR), target recognition, monogenic components, joint sparse representation, discrimination analysis

This paper proposes a method using joint classification of monogenic components with discrimination analysis for target recognition in synthetic aperture radar (SAR) images. Three monogenic components, namely, phase, amplitude, and orientation, are extracted from the original image and classified by joint sparse representation for target recognition. Considering that the three components may have different discrimination capabilities for different operating conditions, the discrimination analysis is incorporated into the classification scheme. The components with low discriminability are not used in the joint classification. Afterwards, those discriminative components for a certain condition are classified to determine the target type. Experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) to evaluate the performance of the proposed method.

The procedure of the proposed method

The procedure of the proposed method

Cite this article as:
Z. Zhang, “SAR Target Recognition via Joint Classification of Monogenic Components with Discrimination Analysis,” J. Adv. Comput. Intell. Intell. Inform., Vol.23 No.3, pp. 414-420, 2019.
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