近年來氣候變遷造成之全球海水面上升對沿海地區已造成嚴重的威脅，因此有效且準確的監測海水面變化已成為一項重要的議題。常見監測海水面變化的方法有潮位站觀測或是透過衛星測高資料實現；然而潮位站觀測量包含地表垂直運動的影響而不能直接求得絕對海水面變化，而衛星測高在沿岸地區存在精度不佳的問題。全球導航衛星系統反射技術（Global Navigation Satellite System Reflectometry, GNSS-R）已被證實可有效應用於監測海水面變化，其透過分析訊噪比(Signal-to-Noise Ratio, SNR)資料中衛星直接訊號與反射訊號的干涉現象推求海水面高度。本研究使用沿岸GNSS測站之訊噪比資料，透過最小二乘頻譜分析(Lomb Scargle Periodogram, LSP)並以調和分析法輔助推求海水面高度。本研究評估使用二階多項式擬合(Quadratic Fitting)、經驗模態分解(Empirical Mode Decomposition, EMD)、總體經驗模態分解(Ensemble Empirical Mode Decomposition, EEMD)及奇異譜分析(Singular Spectrum Analysis, SSA)於訊噪比資料中萃取反射訊號之效益；此外，也針對衛星仰角資料進行對流層折射改正並評估其影響。本研究選用三個具有不同潮差的GNSS連續站進行研究，分別為潮差1公尺的瑞典Onsala Space Observatory (OSO)、3公尺的美國 Friday Harbor、7公尺的法國Brest，並以共站或鄰近潮位站資料進行精度評估。在無折射改正及調和分析之輔助下，瑞典OSO站之GNSS-R解算成果顯示，透過EMD、EEMD及SSA相比二階多項式擬合可顯著提升成果精度，均方根誤差最低可達7.8 公分；美國 Friday Harbor站之GNSS-R解算成果以SSA結果最佳，其成果之均方根誤差為20.0 公分；潮差最大且周遭環境較複雜的法國Brest站則僅有透過SSA之解算成果可行。在採用折射改正及調和分析之輔助下，四種方法在瑞典OSO站及美國 Friday Harbor站之GNSS-R解算成果中之精度無顯著差異，兩站的成果均方根誤差分別為7.3 - 7.9 公分及13.2 - 13.6 公分。法國Brest站之GNSS-R解算成果以SSA之結果為最佳，均方根誤差則可達39.1公分。此外結果也顯示，三種訊號處理方法中以SSA萃取反射訊號所解算之成果最為穩定；SSA可將訊號分解為基於不同頻率的訊號分量並依其重要程度排序，應用於本研究可精確地提取訊噪比資料中的反射訊號，利於後續頻譜分析的判斷且有效提升演算法的穩定度及精準度。

Global warming has caused sea level rise, which has posed great threats to life and property in coastal regions. Therefore, effective and accurate monitoring of sea level changes is a significantly important task. The common methods for monitoring coastal sea level heights (SLH) are based on tide gauges and satellite altimetry. However, the measurements from tide gauges are affected by land motions, while satellite altimetry shows poor accuracy in coastal areas due to waveform contamination and inaccurate geophysical corrections. Global Navigation Satellite System Reflectometry (GNSS-R) based on signal-to-noise ratio (SNR) data has been applied to measure SLH in the past two decades and has been proven useful. In this research, Quadratic Fitting, Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), and Singular Spectrum Analysis (SSA) are adopted for extracting the reflected signals in SNR and analyzing it with Lomb Scargle Periodogram (LSP) assisted with tidal harmonic analysis. In addition, the correction of tropospheric refraction is applied in the GNSS-R model. In this study, three continuous GNSS stations including Onsala Space Observatory (OSO) in Sweden, Friday Harbor in the United States, and Brest in France with the tidal ranges of 1 m, 3 m, and 7 m, respectively, are used. The results are evaluated by comparing with the nearby or co-located tide gauge records. The accuracy of the results without tropospheric refraction correction or tidal harmonic analysis from EMD, EEMD, and SSA with significantly improved compared with that from Quadratic Fitting at OSO. The root-mean-square (RMS) differences are significantly reduced from 20.7 cm to 11.1 cm, 8.2 cm, and 7.8 cm by adopting EMD, EEMD, and SSA, respectively. For Friday Harbor, the result of SSA shows a remarkable improvement with the RMS of 20.0 cm compared to the other three methods. For Brest, where the tidal range is the largest and the surrounding is relatively complicated, only SSA provides reliable results. For the results with tropospheric refraction correction and tidal harmonic analysis, four methods give the results with the RMS at the same level of 7.3 – 7.9 cm and 13.2 – 13.6 cm at OSO and Friday Harbor, respectively. For Brest, the result of SSA shows a remarkable improvement with the RMS of 39.1 cm at Brest. The experimental results show that SSA can provides the most stable solutions among the proposed methods. SSA can not only distinguish signals in different frequencies but also order the signal components according to their eigenvalue, demonstrating the potential to extract the reflected signals from SNR and improve the stability and accuracy of GNSS-R applications.

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