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  • Received: Nov. 28, 2019

    Accepted: Jan. 17, 2020

    Posted: Sep. 1, 2020

    Published Online: Sep. 2, 2020

    The Author Email: He Siyuan (siyuanhe@whu.edu.cn)

    DOI: 10.3788/LOP57.182801

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    Ye Li, Lei Zhang, Siyuan He, Yunhua Zhang, Guoqiang Zhu. Fast Classification Method for Targets Based on Geometric Model[J]. Laser & Optoelectronics Progress, 2020, 57(18): 182801

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Laser & Optoelectronics Progress, Vol. 57, Issue 18, 182801 (2020)

Fast Classification Method for Targets Based on Geometric Model

Li Ye, Zhang Lei, He Siyuan*, Zhang Yunhua, and Zhu Guoqiang

Author Affiliations

  • Electronic Information School, Wuhan University, Wuhan, Hubei 430072, China

Abstract

With the development of synthetic aperture radar (SAR) technology, the amount of data acquired by SAR increases rapidly. When SAR images are used to identify targets, the amount of calculation is large and time-consuming. In order to realize fast and effective recognition of targets, we propose a fast classification method of targets based on geometric model. In this method, binary target region and shadow region are selected as features. First, the forward features are predicted by using the optical visible information of the target geometry model. Then, the binary region extracted from the measured SAR images is aligned with the predicted binary region to establish the correlation. Finally, by judging the similarity criterion, the target classification is realized, and the efficiency and validity of the method are verified on MSTAR data set. Since this method does not involve time-consuming electromagnetic calculation, it can reduce the amount of calculation and accelerate the speed of target recognition.

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