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Optimal polarimetric processing for enhanced target detection

机译:最佳极化处理可增强目标检测

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摘要

The results of a study of several polarimetric target detection algorithms are summarized. The algorithms were tested using real target-in-clutter data collected by the Lincoln Laboratory 35 GHz synthetic aperture radar (SAR) sensor. Fully polarimetric measurements (HH, HV, VV) are processed into intensity imagery using adaptive and nonadaptive polarimetric whitening filters (PWFs). Then a two-parameter constant false alarm rate (CFAR) detector is run over the imagery to detect the targets. Nonadaptive PWF processed imagery is shown to provide better protection performance than either adaptive PWF processed imagery or single-polarimetric-channel HH imagery. In addition, nonadaptive PWF processed imagery is shown to be visually clearer than adaptive processed imagery.
机译:总结了几种极化目标检测算法的研究结果。使用林肯实验室35 GHz合成孔径雷达(SAR)传感器收集的真实杂波中目标数据对算法进行了测试。使用自适应和非自适应极化白化滤镜(PWF)将全极化测量值(HH,HV,VV)处理为强度图像。然后,在影像上运行两参数恒定误报率(CFAR)检测器以检测目标。与自适应PWF处理的图像或单极化通道HH图像相比,非自适应PWF处理的图像可提供更好的保护性能。此外,非自适应PWF处理的图像在视觉上比自适应处理的图像更清晰。

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