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GLRT for two moving target models in multi-aperture SAR imagery

机译:GLRT在多孔径SAR图像中的两个移动目标模型

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It is well known that multi-aperture SAR systems have the capability to detect moving vehicles and to estimate their radial speed and location. A number of techniques for moving target detection and estimation have been proposed in the past. Recently, the Generalized Likelihood Ratio Test (GLRT) approach has been proposed. This paper reviews the GLRT formalism starting from two most common moving target models; one is deterministic and the other stochastic. Assuming that the clutter has Gaussian probability density function (pdf), the same test statistic is derived for both target models.
机译:众所周知,多孔SAR系统具有检测移动车辆的能力并估计其径向速度和位置。 过去已经提出了多种用于移动目标检测和估计的技术。 最近,提出了广义似然比测试(GLRT)方法。 本文评论了从两个最常见的移动目标模型开始的GLRT形式主义; 一个是确定性和另一个随机。 假设杂波具有高斯概率密度函数(PDF),因此为目标模型导出相同的测试统计信息。

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