| Applications of Wavelet Analysis in Differential Propagation Phase Shift Data De-noising |
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| 作者姓名： | HU Zhiqun LIU Liping |
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| 基金项目： | funded by National Natural Science Foundation of China (Grant No. 41375038);China Meteorological Administration Special Public Welfare Research Fund (Grant No. GYHY201306040,GYHY201306075) |
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| 摘 要： | Using numerical simulation data of the forward differential propagation shift （ΦDP） of polarimetric radar,the principle and performing steps of noise reduction by wavelet analysis are introduced in detail.Profiting from the multiscale analysis,various types of noises can be identified according to their characteristics in different scales,and suppressed in different resolutions by a penalty threshold strategy through which a fixed threshold value is applied,a default threshold strategy through which the threshold value is determined by the noise intensity,or a ΦDP penalty threshold strategy through which a special value is designed for ΦDP de-noising.Then,a hard-or soft-threshold function,depending on the de-noising purpose,is selected to reconstruct the signal.Combining the three noise suppression strategies and the two signal reconstruction functions,and without loss of generality,two schemes are presented to verify the de-noising effect by dbN wavelets：（1） the penalty threshold strategy with the soft threshold function scheme （PSS）; （2） the ΦDP penalty threshold strategy with the soft threshold function scheme （PPSS）.Furthermore,the wavelet de-noising is compared with the mean,median,Kalman,and finite impulse response （FIR） methods with simulation data and two actual cases.The results suggest that both of the two schemes perform well,especially when ΦDP data are simultaneously polluted by various scales and types of noises.A slight difference is that the PSS method can retain more detail,and the PPSS can smooth the signal more successfully.
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| 关 键 词： | 小波分析 去噪 应用 传播 差分 阈值函数 相移 有限脉冲响应 |
Applications of wavelet analysis in differential propagation phase shift data de-noising |
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| HU Zhiqun,LIU Liping.Applications of Wavelet Analysis in Differential Propagation Phase Shift Data De-noising[J].Advances in Atmospheric Sciences,2014,31(4):825-835. |
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| Authors: | Zhiqun Hu Liping Liu |
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| Institution: | 1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
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| Abstract: | Using numerical simulation data of the forward differential propagation shift (DP) of polarimetric radar, the principle and performing steps of noise reduction by wavelet analysis are introduced in detail. Profiting from the multiscale analysis, various types of noises can be identified according to their characteristics in different scales, and suppressed in different resolutions by a penalty threshold strategy through which a fixed threshold value is applied, a default threshold strategy through which the threshold value is determined by the noise intensity, or a DP penalty threshold strategy through which a special value is designed for DP de-noising. Then, a hard- or soft-threshold function, depending on the de-noising purpose, is selected to reconstruct the signal. Combining the three noise suppression strategies and the two signal reconstruction functions, and without loss of generality, two schemes are presented to verify the de-noising effect by dbN wavelets: (1) the penalty threshold strategy with the soft threshold function scheme (PSS); (2) the DP penalty threshold strategy with the soft threshold function scheme (PPSS). Furthermore, the wavelet de-noising is compared with the mean, median, Kalman, and finite impulse response (FIR) methods with simulation data and two actual cases. The results suggest that both of the two schemes perform well, especially when DP data are simultaneously polluted by various scales and types of noises. A slight difference is that the PSS method can retain more detail, and the PPSS can smooth the signal more successfully. |
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| Keywords: | polarimetric radar wavelet analysis differential propagation phase shift de-noising |
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