高分辨率SAR对近距离目标ATR的好处

P. Bajcsy, A. R. Chaudhuri
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引用次数: 4

摘要

在这项工作中,我们提出了一种新的提取和匹配算法,能够在高分辨率合成孔径雷达(SAR)数据和邻近目标中执行自动目标识别(ATR)。我们的动机是展示高分辨率SAR对ATR的好处,并扩展ATR算法在扩展操作条件(EOCs)下的目标(例如,近距离目标)的当前能力。提出了一种以点模式表示的目标特征提取算法。每个点的模式提取使用分辨率无关的SAR峰值模型。用新的匹配算法对测试目标和原型目标的特征进行了比较。该匹配算法能够识别一个测试点模式中的多个签名。对近距离目标在多数据分辨率下的ATR性能进行了实验评估。这项工作的贡献在于(a)开发了一种使用分辨率无关的SAR峰值模型的峰值提取算法,(b)设计了一种新的匹配算法,可以在单个测试模式中识别多个签名,(c)在多个数据分辨率下评估接近目标的ATR性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benefits of high resolution SAR for ATR of targets in proximity
In this work we present a new extraction and matching algorithms that enable to perform automatic target recognition (ATR) in high-resolution synthetic aperture radar (SAR) data and targets in proximity. Our motivation was to show benefits of high-resolution SAR for ATR and extend the current capabilities of ATR algorithms for targets in extended operating conditions (EOCs), for example, targets in proximity. We develop a new extraction algorithm for target signatures represented by a point pattern. Each point pattern is extracted using a resolution independent SAR peak model. Test and prototype target signatures are compared with a new matching algorithm. The matching algorithm is capable of identifying multiple signatures in a test point pattern. An experimental evaluation of ATR performance for targets in proximity at multiple data resolution is conducted. The contribution of this work is in (a) developing a peak extraction algorithm that uses a resolution independent SAR peak model, (b) designing a new matching algorithm that can identify multiple signatures in a single test pattern, (c) evaluating ATR performance for targets in proximity at multiple data resolutions.
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