SAR target configuration recognition based on the biologically inspired model
Huang, Xiayuan1; Nie, Xiangli1; Wu, Wei1; Qiao, Hong1; Zhang, Bo2
2017-04-19
发表期刊NEUROCOMPUTING
期号234页码:185-191
文章类型Article
摘要How to extract proper features is very important for synthetic aperture radar (SAR) target configuration recognition. However, most of feature extraction methods are hand-designed and usually can not achieve a satisfactory performance. In this paper, we propose a novel method based on the biologically inspired model to extract features automatically from limited data. Specifically, we learn episodic features (containing the key components and their spatial relations) and semantic features (i.e., semantic descriptions of the key components) which are two important types of features for the human cognition process. Episode features are learned through a deep neural network (DNN) and then semantic geometric features of the key components are defined. Moreover, SAR images are very sensitive to aspect angles. Therefore, we use episode features to estimate aspect angles of testing samples for the final recognition. This paper is a preliminary study and the preliminary experimental results on the moving and stationary target automatic recognition (MSTAR) database demonstrate the effectiveness of the proposed method.
关键词Biologically Inspired Model Sar Target Configuration Recognition Episodic Features Semantic Features Aspect Angle Estimation
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2016.12.054
关键词[WOS]PROPERTY ; CORTEX
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000395221800016
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/14435
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Appl Math, AMSS, Beijing 100190, Peoples R China
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Huang, Xiayuan,Nie, Xiangli,Wu, Wei,et al. SAR target configuration recognition based on the biologically inspired model[J]. NEUROCOMPUTING,2017(234):185-191.
APA Huang, Xiayuan,Nie, Xiangli,Wu, Wei,Qiao, Hong,&Zhang, Bo.(2017).SAR target configuration recognition based on the biologically inspired model.NEUROCOMPUTING(234),185-191.
MLA Huang, Xiayuan,et al."SAR target configuration recognition based on the biologically inspired model".NEUROCOMPUTING .234(2017):185-191.
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