A spectral algorithm for processing staggered-pulse repetition time (SPRT) signals in weather radar is introduced. It includes new approaches for ground clutter filter and hydrometeor spectral moments estimation. The algorithm uses ideas similar to GMAP but applied to non-uniform sampled signals. This work is focused on staggered sequences 2/3, but can be extended to other staggered sequences. Monte Carlo experiments were used to evaluate the performance of the spectral moments estimators for simulated weather signal, in scenarios with and without the presence of ground clutter. When clutter is present, a study using different clutter-to-signal ratios was carried out, showing that the method can deal with a wide range of situations and is appropriate for implementation in real scenarios. A comparison against GMAP-TD was performed, showing similar estimation results for both algorithms and a fivefold processing speed improvement for the proposed method. The performance was also validated using real weather data RMA-12 from a radar located in San Carlos de Bariloche, Argentina. The proposed algorithm has an easy implementation and is a good candidate for real-time implementations.

中文翻译：

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气象雷达中交错信号的自适应频谱处理算法

介绍了一种在气象雷达中处理交错脉冲重复时间（SPRT）信号的频谱算法。它包括用于地面杂波滤波器和水凝气象谱矩估计的新方法。该算法使用类似于GMAP的思想，但适用于非均匀采样信号。这项工作专注于交错序列2/3，但可以扩展到其他交错序列。在存在和不存在地面杂波的情况下，使用蒙特卡洛实验来评估用于模拟天气信号的频谱矩估计器的性能。当存在杂波时，进行了使用不同杂波信号比的研究，结果表明该方法可以处理多种情况，适合在实际场景中实施。与GMAP-TD进行了比较，展示了两种算法的相似估计结果，并且所提方法的处理速度提高了五倍。使用来自阿根廷圣卡洛斯·德巴里洛切的雷达的真实天气数据RMA-12也对性能进行了验证。所提出的算法易于实现，并且是实时实现的良好候选者。