马聪慧2,,
丁柏圆3,
宋海波1
1.国防科技大学电子科学学院自动目标识别重点实验室 长沙 410073
2.航天工程大学 北京 101416
3.解放军96901部队25分队 北京 100094
基金项目:国家部委基金
详细信息
作者简介:文贡坚(1972–)，男，湖南宁乡人，教授，博士生导师，研究方向为遥感图像处理
马聪慧(1987–)，女，湖北襄阳人，博士，讲师。2017年在国防科技大学电子工程学院获得博士学位，现担任航天工程大学讲师。主要研究方向为SAR目标识别。E-mail: ma_conghui@yeah.net
丁柏圆(1990–)，男，安徽池州人，博士。2018年在国防科技大学电子工程学院获得博士学位，现为96901部队助理研究员。研究方向为SAR自动目标识别
宋海波(1992–)，男，内蒙古呼伦贝尔人，博士生。主要研究方向为SAR自动目标识别，特征提取
通讯作者:文贡坚 wengongjian@sina.com
责任主编：邢孟道 Corresponding Editor: XING Mengdao中图分类号:TN957
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被引次数:0
出版历程
收稿日期:2020-07-08
修回日期:2020-08-19
网络出版日期:2020-08-26
SAR Target Physics Interpretable Recognition Method Based on Three Dimensional Parametric Electromagnetic Part Model
WEN Gongjian1,,,MA Conghui2,,
DING Baiyuan3,
SONG Haibo1
1. National Key Laboratory of Science and Technology on Automatic Target Recognition, College of Electronic Science, National University of Defense Technology, Changsha 410073, China
2. Space Engineering University, Beijing 101416, China
3. Unit 96901 of People’s Liberation Army, Beijing 100094, China
Funds:The National Minstries Foundation
More Information
Corresponding author:WEN Gongjian, wengongjian@sina.com
摘要
摘要:该文通过部件级三维参数化电磁模型(3D-PEPM)描述了复杂目标的电磁散射现象，并基于此模型提出了一种新的合成孔径雷达(SAR)目标识别方法。该方法首先根据雷达参数将3D-PEPM中各个散射体的散射响应投影到二维图像平面，预测每个散射体的位置和形状，然后根据3D-PEPM提供的先验信息评估3D-PEPM与SAR数据之间的相似程度，最后利用一种视角调整方法对整个过程进行优化，产生3D-PEPM和SAR数据之间的最终匹配分数，并根据该匹配分数完成识别决策。这种识别方法明确标识了SAR数据和3D-PEPM散射体之间的对应关系，具有清晰的物理可解释性，能够有效处理各种扩展条件下的SAR目标识别问题，仿真实验验证了该方法的有效性。
关键词:合成孔径雷达/
目标识别/
部件级/
三维参数化电磁模型/
物理可解释性
Abstract:In this paper, a target’s electromagnetic scattering phenomenon is characterized by the Three Dimensional Parametric Electromagnetic Part Model (3D-PEPM) and a novel Synthetic Aperture Radar (SAR) target recognition method is proposed based on the model. The proposed method projects the individual scatterers in the 3D-PEPM to the 2D image plane to predict the location and appearance for each scatterer according to the radar parameters firstly. Then based on the prior information provided by the 3D-PEPM, the similarities between the 3D-PEPM and SAR data are evaluated. Finally, a view angle adjusting method is utilized to optimize the whole process to produce the final match score between the model and SAR data, and the recognition decision is made according to the match score. The proposed recognition method identifies clearly the correspondences of the scatterers between SAR data and 3D-PEPM and enjoys the explicit physical interpretability, so it can deal with SAR recognition problems under various extended operating conditions. Experiments on simulated data reveal the effectiveness of the proposed method.
Key words:Synthetic Aperture Radar (SAR)/
Target recognition/
Part level/
Three dimensional parametric electromagnetic model/
Physics interpretable
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