VHF雷達濾除飛機訊號與風場研究-希爾伯特-黃轉換之應用

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Title:	VHF雷達濾除飛機訊號與風場研究-希爾伯特-黃轉換之應用
Authors:	張元瀚;Chang, Yuan-Han
Contributors:	太空科學與工程研究所
Keywords:	希爾伯特-黃轉換;VHF特高頻雷達;HHT
Date:	2021-07-22
Issue Date:	2021-12-07 11:18:18 (UTC+8)
Publisher:	國立中央大學
Abstract:	中壢特高頻(VHF,52MHz)雷達站，約位於桃園國際機場南方12公里處，因其座落飛機航班之起降航道上，故在執行大氣觀測時，飛機回波時常成為污染資料品質的原因之一，而[洪萱芸, 2020]首次提出使用希爾伯特-黃轉換(Hilbert-Huang Transform, HHT)濾除飛機回波的演算法，該演算法可大幅提升觀測資料品質，且濾除效果遠優於小波轉換(Wavelet Transform)的結果，然而此方法僅限於垂直波束的晴空觀測結果。此外，其也尚未實際將濾除過後的資料應用於Velocity-Azimuth Display (VAD)技術計算的三維風場、雨滴粒徑分布..等雷達資料之推演，因此本論文嘗試尋找希爾伯特-黃轉換(HHT)演算法中可應用於大氣晴空觀測中傾斜波束的參數，而後將由演算法濾除之結果經VAD技術計算後，與氣象局剖風儀雷達(449MHz)進行比較，並探討濾除後的實用性。經分析此演算法濾除飛機時會保留低頻分量，其中若飛機訊號存在低頻波或者在執行經驗模態分解(EMD)時有混波的問題，則會導致在頻譜中低頻出現極為異常的強烈訊號。為了解決此問題，本研究修改了演算法，並且改以使用DC項取代飛機訊號，將飛機訊號所對應時間的實部(In-Phase, I)與虛部(Quadrature, Q)使用DC項取代，而尋找飛機訊號的時間仍使用希爾伯特-黃轉換(HHT)，藉此規避上述問題。最後比較「無使用希爾伯特-黃轉換濾除」、「希爾伯特-黃轉換濾除」與「DC項取代法」三者之風場結果與剖風儀風場的相關性(Correlation Coefficient, C.C.)以及方均根誤差(root-mean-square error, RMSE)。整體而言，經過「希爾伯特-黃轉換濾除」與「DC項取代法，其相關性及方均根誤差與「無濾除」相比，皆明顯改善，但若是與「無飛機影響」的情況比較，且皆經過品質控管的結果，「濾除」與「DC項取代法」的相關性以及方均根誤差與「無飛機影響」相比，仍有改善空間。而在有飛機影響下，更進一步將「濾除」與「DC項取代法」相互比較，兩方法不相上下，其中，「DC項取代法」後能正確判斷亂流都卜勒速度的資料點數會多於「濾除」後，且在視覺上該方法的頻譜圖比「濾除」後更為合理，故仍推薦「DC項取代法」用以改善飛機之影響，亦可增加受飛機影響之大氣觀測資料的實用程度。 ;The distance between the Chunge-Li VHF radar station and Taiwan Taoyuan International Airport is about 12km. In the meanwhile, the Chunge-Li VHF radar station locates in the lane of the taking-off or landing airplane. When the missions of observing the atmosphere are performed by Chunge-Li VHF radar, the echo signal is always polluted by the echo power of the crossing-radar-beam airplane, so the quality of the atmospheric data would be influenced and low quality. However, in the paper, [洪萱芸, 2020], an algorithm was proposed firstly. The algorithm can filter out the signal of airplane by Hilbert-Huang Transform (HHT). The result of the algorithm is better than the result by using Wavelet Transform. The algorithm greatly improves the quality of the observation data. However, the condition is only for the vertical beam and the result of the algorithm isn’t applied to be calculated the 3-D wind field by Velocity-Azimuth Display (VAD) technology、raindrop size distribution …etc. Thus, this study attempts to find the adapting parameter in the algorithm to apply in the observation of the oblique beam. After the aircraft echo is filtered out, the result will try to calculate the 3-D wind field by Velocity-Azimuth Display (VAD) technology. Finally, the wind field would be compared with Central Weather Bureau wind profiler(449MHz) result, and the application would be further discussed. Through the algorithm, the high frequency component of aircraft echo would be filtered out. However, if the aircraft echo contained the low-frequency component or the problem of mixing wave from doing Empirical Mode Decomposition (EMD), there would be anomalous strong signal at low-frequency of the spectrum. With these problems, the algorithm should be modified. The way is that, with the DC terms of the real part (In-Phase, I) and imaginary part (Quadrature, Q), the amplitude at the time of aircraft echo on the I and Q is replaced. The time of aircraft echo is still detected by the HHT. This algorithm is named “DC term replacement”. Finally, the root-mean-square error(RMSE) and correlation coefficient between the 3-D wind field by “filtering out by HHT” or “DC term replacing” and the wind field of the Central Weather Bureau (CWB) wind profiler can be calculated. In the meanwhile, two indexes between the wind field before filtered out and the wind field of CWB wind profiler can also be calculated. A comparison with two parameters of three different conditions would be made. Not only “filtering out” but also “DC term replacing” result can be more greatly improved than the result before filtered out. To the other condition, the comparison between “no aircraft”、“filtering out” and “DC term replacing” should be made. The results of “filtering out” and “DC term replacing” still need to be improved by comparing with the result of “no aircraft”. To the results of “filtering out” and “DC term replacing”, it is comparable each other. But, visually, the spectrum of “DC term replacement” is more reasonable. Eventually, DC term replacement would be recommended. The distance between the Chunge-Li VHF radar station and Taiwan Taoyuan International Airport is about 12km. In the meanwhile, the Chunge-Li VHF radar station locates in the lane of the taking-off or landing airplane. When the missions of observing the atmosphere are performed by Chunge-Li VHF radar, the echo signal is always polluted by the echo power of the crossing-radar-beam airplane, so the quality of the atmospheric data would be influenced and low quality. However, in the paper, [洪萱芸, 2020], an algorithm was proposed firstly. The algorithm can filter out the signal of airplane by Hilbert-Huang Transform (HHT). The result of the algorithm is better than the result by using Wavelet Transform. The algorithm greatly improves the quality of the observation data. However, the condition is only for the vertical beam and the result of the algorithm isn’t applied to be calculated the 3-D wind field by Velocity-Azimuth Display (VAD) technology、raindrop size distribution …etc. Thus, this study attempts to find the adapting parameter in the algorithm to apply in the observation of the oblique beam. After the aircraft echo is filtered out, the result will try to calculate the 3-D wind field by Velocity-Azimuth Display (VAD) technology. Finally, the wind field would be compared with Central Weather Bureau wind profiler(449MHz) result, and the application would be further discussed. Through the algorithm, the high frequency component of aircraft echo would be filtered out. However, if the aircraft echo contained the low-frequency component or the problem of mixing wave from doing Empirical Mode Decomposition (EMD), there would be anomalous strong signal at low-frequency of the spectrum. With these problems, the algorithm should be modified. The way is that, with the DC terms of the real part (In-Phase, I) and imaginary part (Quadrature, Q), the amplitude at the time of aircraft echo on the I and Q is replaced. The time of aircraft echo is still detected by the HHT. This algorithm is named “DC term replacement”. Finally, the root-mean-square error(RMSE) and correlation coefficient between the 3-D wind field by “filtering out by HHT” or “DC term replacing” and the wind field of the Central Weather Bureau (CWB) wind profiler can be calculated. In the meanwhile, two indexes between the wind field before filtered out and the wind field of CWB wind profiler can also be calculated. A comparison with two parameters of three different conditions would be made. Not only “filtering out” but also “DC term replacing” result can be more greatly improved than the result before filtered out. To the other condition, the comparison between “no aircraft”、“filtering out” and “DC term replacing” should be made. The results of “filtering out” and “DC term replacing” still need to be improved by comparing with the result of “no aircraft”. To the results of “filtering out” and “DC term replacing”, it is comparable each other. But, visually, the spectrum of “DC term replacement” is more reasonable. Eventually, DC term replacement would be recommended.
Appears in Collections:	[Graduate Institute of Space Science] Department of Earth Sciences

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