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System and method for processing data in weather radar

机译:天气雷达中的数据处理系统和方法

摘要

Systems and methods that adapt to the weather and clutter in a weather radar signal and apply a frequency domain approach that uses a Gaussian clutter model to remove ground clutter over a variable number of spectral components that is dependent on the assumed clutter width, signal power, Nyquist interval and number of samples. A Gaussian weather model is used to iteratively interpolate over the components that have been removed, if any, thus restoring any overlapped weather spectrum with minimal bias caused by the clutter filter. The system uses a DFT approach. In one embodiment, the process is first performed with a Hamming window and then, based on the outcome, the Hamming results are kept or a portion of the process is repeated with a different window. Thus, proper windows are utilized to minimize the negative impact of more aggressive windows.
机译:适应天气雷达信号中的天气和杂波并应用频域方法的系统和方法,该方法使用高斯杂波模型来消除取决于假设杂波宽度,信号功率,可变频谱分量的地面杂波奈奎斯特间隔和样本数。使用高斯天气模型对已删除的组件(如果有)进行迭代插值,从而以杂波滤波器引起的最小偏差恢复任何重叠的天气谱。该系统使用DFT方法。在一个实施例中,首先用汉明窗执行该过程,然后基于结果,保持汉明结果或用不同的窗重复该过程的一部分。因此,利用适当的窗口来最小化更具侵略性的窗口的负面影响。

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