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

C. Clemente, L. Pallotta, I. Proudler, A. De Maio, J. Soraghan, A. Farina
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引用次数: 2

Abstract

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.
基于伪泽尼克矩的多传感器全极化SAR自动目标识别
在现代战场场景中,可以利用多种信息来源来减轻不确定性。极化和空间分异可以为特定和关键任务提供有用的信息,如自动目标识别(ATR)。本文介绍了伪泽尼克矩在全极化Gotcha数据集上的应用。通过使用多次观察,具体地改进了单平台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。
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