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Ground Clutter Detection Using the Statistical Properties of Signals Received With a Polarimetric Radar

机译:利用极化雷达接收信号的统计特性检测地物杂波

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Polarimetric weather radars provide additional measurements that allow better characterization of the targeted medium. Because ground clutter has different polarimetric characteristics from weather echoes, dual-polarization measurements can be used to distinguish one from the other. Ground clutter and weather signals also have different statistical properties which can be utilized to distinguish one from the other. A test statistic, obtained from the generalized likelihood ratio test (GLRT), and a simple Bayesian classifier (SBC), with inputs from the mean and covariance of the received signals, are developed to detect ground clutter in the presence of weather signals. It is found that the test statistic produces false detections caused by narrow-band zero-velocity weather signals while the SBC can effectively neutralize them. This work is aimed at detecting ground clutter based solely on data from each resolution volume. The performances of the test statistic and SBC are shown by applying them to radar data collected with the University of Oklahoma-Polarimetric Radar for Innovation in Meteorology and Engineering.
机译:极化气象雷达提供了额外的测量值,可以更好地表征目标介质。由于地物杂波具有与天气回波不同的极化特性,因此可以使用双极化测量将它们彼此区分开。地面杂波和天气信号也具有不同的统计属性,可用于区分彼此。通过广义似然比检验(GLRT)和简单贝叶斯分类器(SBC)获得的检验统计数据,以及来自接收信号均值和协方差的输入,可开发用于检测天气信号存在时的地面杂波。发现测试统计数据会产生由窄带零速天气信号引起的错误检测,而SBC可以有效地抵消它们。这项工作旨在仅基于来自每个分辨率体积的数据来检测地面杂波。通过将测试统计数据和SBC的性能应用于俄克拉荷马大学用于气象和工程创新的测压雷达收集的雷达数据,可以显示出它们的性能。

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