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Incoherent detection of man-made objects obscured by foliage in forest area

机译:森林区域被树木遮挡的人造物体的非相干检测

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The paper introduces a new likelihood ratio test (LRT) for incoherent detection of man-made objects obscured by foliage in forest area. The test is performed to detect changes between a reference image and a surveillance image. The method is developed for change detection in high resolution Synthetic Aperture Radar (SAR). For simplicity and lack of more appropriate models, the new LRT is still based on simple and efficient models. If there is no man-made object, the statistical model for clutter and noise of two images will be a bivariate Rayleigh distribution. In contrary, a joint distribution of Rayleigh and uniform is used to model for target, clutter, and noise. The proposed LRT is evaluated using radar data acquired by CARABAS in northern Sweden. The probability of detection is up to 96% with much less than one false alarm per square kilometer.
机译:本文介绍了一种新的似然比测试(LRT),用于对森林区域被树叶遮挡的人造物体进行非相干检测。执行该测试以检测参考图像和监视图像之间的变化。该方法专为高分辨率合成孔径雷达(SAR)中的变化检测而开发。为了简化和缺乏更合适的模型,新的LRT仍然基于简单有效的模型。如果没有人造物体,则两个图像的杂波和噪声的统计模型将是双变量瑞利分布。相反,瑞利和统一的联合分布用于对目标,杂波和噪声进行建模。使用瑞典北部CARABAS采集的雷达数据对拟议的轻轨系统进行了评估。探测到的概率高达96%,而每平方公里的误报次数则少得多。

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