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Multi-sensor full-polarimetric SAR Automatic Target Recognition using pseudo-Zernike moments

机译:使用伪Zernike矩的多传感器全极化SAR自动目标识别

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In the modern battlefield scenario multiple sources of information may be exploited to mitigate uncertainty. Polarization and spatial diversity can provide useful information for specific and critical tasks such as the Automatic Target Recognition (ATR). In this paper the use of pseudo-Zernike moments applied to the full-polarimetric Gotcha dataset is presented. Specifically improved single platform ATR performance is demonstrated through the use of multiple observations.
机译:在现代战场场景中,可以利用多种信息源来减轻不确定性。极化和空间分集可以为特定任务和关键任务(例如自动目标识别(ATR))提供有用的信息。本文提出将伪Zernike矩应用于全极化Gotcha数据集。通过使用多个观察结果,可以具体证明单个平台的ATR性能得到了改善。

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