Deep kernel learning method for SAR image target recognition

Xiuyuan Chen; Xiyuan Peng; Ran Duan; Junbao Li

doi:10.1063/1.4993064

Deep kernel learning method for SAR image target recognition

Rev Sci Instrum. 2017 Oct;88(10):104706. doi: 10.1063/1.4993064.

Authors

Xiuyuan Chen¹, Xiyuan Peng¹, Ran Duan², Junbao Li¹

Affiliations

¹ Automatic Test and Control Institute, Harbin Institute of Technology, Harbin 150080, China.
² Beijing Aerospace Automatic Control Institute, Beijing 100854, China.

PMID: 29092528
DOI: 10.1063/1.4993064

Abstract

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.