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Thunderstorm Recognition Algorithm Research Based on Simulated Airborne Weather Radar Reflectivity Volume Scan Data

机译:雷暴识别算法基于模拟空气雷达反射率扫描数据的研究

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At present, most airborne radars have no volume scan capability, so the echo information detected is limited and it can be difficult to detect the thunderstorms in front of the aircraft completely. First of all. this paper proposes an airborne weather radar that adopts volume scan mode and takes the X-band ground-based weather radar data as the simulation source to obtain the airborne radar reflectivity volume scan data according to a simulation model. Then, based on the Storm Cell Identification (SCI) algorithm, this paper researches and proposes a thunderstorm identification algorithm applying to this airborne radar by modifying some threshold parameters, which has improvements on identifying thunderstorm cells. Finally, an example of thunderstorm identification based on the simulated airborne weather radar reflectivity volume scan data is given, which shows that the algorithm can effectively identify the thunderstorm cells in the scanning sector in front of the radar and get their attributes. It is helpful for monitoring thunderstorm and meaningful for flight safety.
机译:目前,大多数机载雷达没有体积扫描能力,因此检测到的回声信息受到限制,并且可能难以完全检测飞机前面的雷雨。首先。本文提出了一种采用体积扫描模式的机载气象雷达,并采用X波段地基天气雷达数据作为模拟源,以根据仿真模型获得空中雷达反射率扫描数据。然后,基于风暴细胞识别(SCI)算法,本文通过修改一些阈值参数来研究对该机载雷达的雷暴识别算法,其在识别雷暴细胞的改进。最后,给出了基于模拟的空气传播天气雷达反射率扫描数据的雷暴识别的示例,表明该算法可以有效地识别雷达前面的扫描扇区中的雷暴单元并获得其属性。有助于监控雷暴和有意义的飞行安全。

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