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Efficient end-to-end feature-based system for SAR ATR

机译:用于SAR ATR的高效基于结束功能的系统

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In this paper we discuss an end-to-end system for SAR automatic target recognition (ATR), giving particular emphasis to the discrimination and classification stages. The ATR system employs a three sequential stage approach to reduce complexity: a detection stage, a discrimination stage, and a classification stage. Details of the detection stage were presented previously. The target discrimination and classification methods, which we present here, involve extracting rotationally and translationally invariant features from the Radon transform of target chips. The methods are applied in both isolated and complete end-to-end systems on the TESAR baseline SAR database distributed by the U.S. Army Research Laboratory and in isolation using the public MSTAR database. The performance results on these SAR datasets are presented.
机译:在本文中,我们讨论了SAR自动目标识别(ATR)的端到端系统,特别强调歧视和分类阶段。 ATR系统采用三个顺序阶段方法来降低复杂性:检测阶段,辨别阶段和分类阶段。先前呈现了检测阶段的细节。我们在此呈现的目标歧视和分类方法涉及从目标芯片的氡变换旋转和平移的不变特征。这些方法适用于由美国陆军研究实验室的TESAR基线SAR数据库的分离和完整的端到端系统,并使用公共MSTAR数据库隔离。呈现了这些SAR数据集的性能结果。

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