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研究生:邱文豪
研究生(外文):Wen-Hou Cho
論文名稱:波列分析在低層MST雷達回波訊號之應用
論文名稱(外文):DOPPLER FLUCTUATION OF VHF RADAR SIGNAL INTERPRETED BY WAVELETS
指導教授:劉兆漢,符一如
指導教授(外文):C.H.Liu and I.J.Fu
學位類別:碩士
校院名稱:國立中央大學
系所名稱:太空科學研究所
學門:自然科學學門
學類:天文及太空科學學類
論文種類:學術論文
論文出版年:1996
畢業學年度:84
語文別:中文
論文頁數:90
中文關鍵詞:中壢雷達大氣MSTWAVELETS
外文關鍵詞:Chung-LiMSTVHFRadarWavelets
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傳統之MST雷達回波訊號處理常用方法(FFT,相關函數法),往往假設回
波訊號為常定的。對於時間上訊息的取得,短時間傅氏分析雖幫助不小,
然窗函數的大小卻嚴重影響了分析結果的取向。具"覆解析"功能的波列分
析提供了一個新的方法來同時獲得時間與頻率上的資訊分析,對於我們探
討大氣動力頗有幫助。波列分析對大氣 MST雷達回波訊號的分析結果,顯
示了大氣散射子的斷續存在大氣中。同時我們也發現: 1)利用波列分析
的統計性質,將不會與傳統處理方法相違背。 2)波列分析為大氣動力的
探討提供一個不須以統計為前提的理論基礎。 3)波列分析的相位可以幫
助我們將大氣動力的探討做深入的區別散射子在雷達體積內之各種狀態。
當區別散射子在雷達體積內之各種狀態是可能時,對於大氣渦流的動力探
討將更是指日可待。

In the conventional MST radar echo signals analysis methods,
FFT and correlation functions, assume the turbulence wind
field to be stationary. Although the STFT ( short time Fourier
trans- form ) provided some help to get more about the time
dependent information, the window selection unfortunately
affects the re- sult. The multi-resolution of wavelets
transform provides a new way, to interpret the radar signals
with different time and frequency scales, to get more
information of MST observation of atmospheric dynamics .
Analyzing the Doppler velocity, the time dependent turbulent
fluctuation can be clearly identified by the wavelets
transform. And it also provides us the dynamical procedure of
turbulent. In this report, we show that the irregularity of the
atmosphere is intermittent with time in the radar volume , we
also find that: (1)Wavelets transform is compared well with the
conventional analyzing methods in the MST radar atmosphere
observations. (2)The Wavelets transform provides us an
analyzing basis to the MST radar signals without the assumption
of stationality and with the property of statistic. (3)The
phase of the Wavelet transform provides us a new way to follow
the temporal variation of the amplitude of different Doppler
frequencies. Since the intermittence of the atmosphere back
scattering is decomposition, the temporal turbulent mechanism
is hopeful to be solved. And this leads to the question of the
"universal spectrum" if is meaningful with the assumption of
homogenous and stationary by Kolmogrove. In the future, the
mechanism causing these variations may be identified more
easily by this technique. And the ability of mullet-resolution
the wavelet an- alysis may lead us to the fractal structure of
the atmosphere.

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