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首页> 外文期刊>International Journal of Engineering Research and Applications >Denoising of Spectral Data Using Complex Wavelets
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Denoising of Spectral Data Using Complex Wavelets

机译:使用复数小波对光谱数据进行去噪

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摘要

Atmospheric signal processing is of interest to many scientists, where there is scope for the development of new and efficient tools for cleaning the spectrum, detection, and estimation of parameters like zonal (U), meridional (V ), wind speed (W), etc. This paper deals with a signal processing technique for the cleansing of spectrum, based on the complex wavelets with custom thresholding, by analyzing the Mesosphere¨CStratosphere¨CTroposphere radar data that are backscattered from the atmosphere at high altitudes and severe weather conditions with low signal-to-noise ratio. The proposed algorithm is self-consistent in detecting wind speeds up to a height of 18 km, in contrast to the existing method which estimates the Doppler manually and fails at higher altitudes. The results have been validated using the Global Positioning System sonde data
机译:大气信号处理是许多科学家感兴趣的领域,在这里有开发新的有效工具的空间,这些工具可用于清洁频谱,检测和估算诸如纬向(U),子午(V),风速(W),本文通过分析具有自定义阈值的复杂小波,通过分析在高海拔和恶劣天气条件下从大气反向散射的中层C层,平流层,C层大气层雷达数据,研究了一种用于频谱净化的信号处理技术。信噪比。与现有方法手动估计多普勒频率并在更高的海拔高度下失败的现有方法相比,该算法在检测高达18 km的风速时是自洽的。结果已使用全球定位系统探空仪数据验证

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