优化极化处理增强目标检测

Leslie M. Novak, M. Burl, W. W. Irving
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引用次数: 356

摘要

介绍了几种极化目标检测算法的研究结果。该研究涉及林肯实验室毫米波SAR传感器,这是一种全极化、35 GHz合成孔径雷达。使用自适应和非自适应偏振增白滤波器(pwf)将全偏振测量值(HH, HV, VV)处理成强度图像,并量化散斑减少量。然后在图像上运行一个双参数CFAR(恒定虚警率)检测器来检测目标。非自适应PWF处理图像比自适应PWF处理图像或单偏振通道HH图像提供更好的检测性能。此外,非自适应PWF处理的图像在视觉上比自适应PWF处理的图像更清晰。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal polarimetric processing for enhanced target detection
The results of a study of several polarimetric target detection algorithms are presented. The study concerns the Lincoln Laboratory millimeter-wave SAR sensor, a fully polarimetric, 35 GHz synthetic-aperture radar. Fully polarimetric measurements (HH, HV, VV) are processed into intensity imagery using adaptive and nonadaptive polarimetric whitening filters (PWFs), and the amount of speckle reduction is quantified. Then a two-parameter CFAR (constant false alarm rate) detector is run over the imagery to detect the targets. Nonadaptive PWF processed imagery is shown to provide better detection 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 PWF processed imagery.<>
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