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A parametric spectral moments estimation algorithm based on fitting autocorrelation sequence

机译:基于拟合自相关序列的参数化谱矩估计算法

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The first three spectral moments of weather radar echoes are closely correlative with the types and characteristics of meteorological phenomena. The weather echoes and ground clutter have power spectra with shape following closely to Gaussian function. The first three spectral moments can be estimated using the modelled autocorrelation function. A parametric spectral moment estimator is proposed based on fitting the autocorrelation sequence. And the RELAX is used to deal with the scenarios of two or more mixed Gaussian spectrums. Finally, experimental results with simulated weather radar signals and performance analysis demonstrate that the present estimator is efficient with higher resolution.
机译:天气雷达回波的前三个频谱矩与气象现象的类型和特征密切相关。天气回波和地面杂波具有与高斯函数密切相关的形状的功率谱。可以使用建模的自相关函数来估计前三个频谱矩。在拟合自相关序列的基础上,提出了一种参数化谱矩估计器。 RELAX用于处理两个或多个混合高斯频谱的情况。最后,模拟天气雷达信号和性能分析的实验结果表明,该估计器是有效的,具有较高的分辨率。

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