限定像素用于属性散射中心提取

J. Farmer, M. Saville
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引用次数: 1

摘要

利用共极化和交叉极化相历史数据可以增强合成孔径雷达(SAR)数据的特征提取。最近的光谱分割链接图像测试工作使用偏振和基于傅里叶的峰值检测来从SAR相位历史数据中提取属性散射中心(ASC)。由于只能检测到占主导地位的散射体,导致有关目标的信息不完整,因此对间隔较近的散射中心的提取受到影响。我们提出了一种类似于SPLIT算法的基于二维proony方法和全极化SAR相位历史的ASC提取方法。在这项工作中,我们比较了使用反向投影成像算子和使用二维proony方法时的信号参数估计性能。我们还使用原始形状的实验来检验特征估计的性能,原始形状可以表示目标分类所需的复杂特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Qualifying pixels for attributed scattering center extraction
Use of co- and cross-polarization phase history data has been shown to enhance feature extraction from synthetic aperture radar (SAR) data. Recent work with the spectrum-parted linked image test uses polarization with Fourier-based peak detection to qualify pixels for attributed scattering center (ASC) extraction from SAR phase history data. Extraction of closely spaced scattering centers suffers because only the dominant scatterer can be detected resulting in incomplete information about the object. We propose an ASC extraction method based on 2D Prony method and fully polarimetric SAR phase history similar to the SPLIT algorithm. In this work, we compare the signal parameter estimation performance when using a back-projection imaging operator to that when using 2D Prony method. We also examine the performance of feature estimation using experiments of primitive shapes that could represent a complicated feature needed for target classification.
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