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研究生:余徐維
研究生(外文):Syu-Wei Yu
論文名稱:應用長期連續GPS觀測資料於坐標參考框架變異之研究
論文名稱(外文):A Study on Reference Frame Variations Based on Long-term GPS Measurements
指導教授:韓仁毓韓仁毓引用關係
指導教授(外文):Jen-Yu Han
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:土木工程學研究所
學門:工程學門
學類:土木工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:77
中文關鍵詞:全球定位系統坐標參考框架變形分析動態坐標框架轉換
外文關鍵詞:Global positioning system.Reference FrameDeformation AnalysisTime-variant Transformation
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  • 被引用被引用:3
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根據板塊運動理論,地球表面可分為數個剛體板塊,板塊之間每年以數公厘至數公分不等之速率相互移動,因此由地表控制點位所定義之坐標參考框架也會隨時間而變動。以往透過傳統測量方式並無法得到地表點位之連續細微變化,但隨著現代科技的發展與衛星大地測量技術的進步,加上全球定位系統( Global Positioning System, GPS )的問世,可對地表點位進行長期連續的觀測,有效偵測地表動態行為,進而解算出點位空間資訊。而在不同時期或使用不同測量技術經觀測解算得到之坐標與速度場,其所依據之參考框架定義亦不盡相同,一般可透過以相似轉換為基礎之動態框架轉換模型,對不同坐標參考框架進行轉換,使其具有共同基準,以利後續應用。
本研究主要目的為建立一套完整的動態框架轉換模型參數估計程序,包含從GPS原始觀測資料的處理開始,透過完整的GPS定位解算以及序列資料處理流程,以獲得高品質的地表動態資料,作為後續應用之可靠依據;並採用嚴謹的參數估計平差模型(包含廣義平差模型與虛擬觀測平差模型),選擇合適之動態框架轉換模型進行轉換參數估計,評估參數顯著性,在不設限參考框架變異行為的情況下,期望能夠透過這套流程有效建立變形框架間之動態轉換關係。
根據數值成果顯示,在以台灣GPS衛星追蹤站2001年至2007年RINEX資料作為分析基礎下,本研究所建立的序列資料處理流程能夠顯著地提升所獲得的地表動態行為估計品質,此外由於台灣地區地表點位存在不均勻的變形行為,若以現有動態相似轉換模型加以模式,將會降低坐標及速度場轉換品質,而動態仿射轉換模型則因為其可以有效處理非均勻變形場,對於台灣地區動態框架轉換參數之顯著性以及坐標、速度場之轉換品質均將有明顯助益,可做為未來在變形區域建立動態坐標系統時之主要參考模型。
According to the tectonic theory, the Earth’s surface can be divided into several rigid plates which move with respect to each other with velocities from millimeters to centimeters per year. Consequently, the coordinates of ground control points defining a terrestrial reference frame will also vary with time. In the past, detecting the tiny surface movements using traditional surveying technique is not an easy task. In recent years, with the advance of space geodesy techniques and the application of the Global Positioning System ( GPS ), the dynamical behavior of the Earth’s surface can be continuously observed and precisely determined. As soon as the time-variant coordinates and velocities of ground control points can be estimated, the geometric relations between terrestrial reference frames at different epochs can be established using a time-variant reference frame transformation model.
The purpose of this study is to develop a complete procedure for establishing a time-variant reference frame transformation model. First, the high quality information for the coordinates and velocities of ground control stations are obtained by an integrated GPS data processing and time-series improvement procedure. Then a rigorous parameter estimation approach ( including a general and a unified least-squares techniques ) is proposed for estimating the parameters of different time-variant transformation models. The estimated parameters are tested for their statistical significance and the actual geometric relations between time-variant reference frames can thus be identified.
In the numerical analysis, the RINEX data from 2001 to 2007 of seven GPS tracking stations in Taiwan area has been processed and analyzed. The results show that the quality of the velocity estimations can be significantly improved by applying the proposed time-series improvement approach. Furthermore, due to the non-uniform deformations in this area, a time-variant similarity transformation model does not provide an acceptable result. On the other hand, a time-variant affine transformation model can produce a coordinate and velocity transformation of a higher quality due to its capability on modeling non-uniform deformations. Consequently, a time-variant affine transformation model can serve as an eligible candidate model especially in establishing a time-variant reference system in a deforming area.
口試委員審定書 i
誌謝 ii
摘要 iv
Abstract vi
目錄 vii
圖目錄 ix
表目錄 xi
第一章 緒論 1
1-1 研究背景 1
1-2 研究動機與目的 9
1-3 研究方法 10
1-4 論文架構 12
第二章 動態框架轉換模型相關研究 13
2-1 動態框架轉換模型 13
2-2 全球性參考框架轉換之應用 14
2-3 全球性與區域性參考框架轉換之應用 14
第三章 動態框架轉換模型 17
3-1 動態相似轉換模型( Time-variant similarity transformation model ) 17
3-1-1數學模型 17
3-1-2 參數估計方式 19
a. 參數估計 20
b. 參數率估計 22
c. 精度估計 24
3-2 動態仿射轉換模型( Time-variant affine transformation model ) 25
3-2-1數學模型 25
3-2-2參數估計方法 29
a. 參數估計 29
b. 參數率估計 29
c. 精度估計 29
d. 主成分參數誤差傳播 29
3-3 數值模擬實驗 31
第四章 長期連續GPS資料處理與分析 36
4-1 GPS資料解算 36
4-2 GPS序列資料品質提升 39
4-2-1 不連續運動偵測 41
4-2-2 速度場估計 42
4-2-3 粗差偵測 43
4-2-4 週期訊號處理 44
4-2-5 統計檢定 45
4-3序列資料品質提升範例說明 47
第五章 實際資料數值分析成果 53
5-1 台灣追蹤站坐標與速度場解算成果 53
5-2 動態框架轉換模型參數估計 57
5-2-1 動態框架轉換模型參數估計(全區) 57
5-2-2 動態框架轉換模型參數估計(五站) 61
5-3 數值成果分析 67
第六章 結論與建議 70
6-1 結論 71
6-2 建議 72
參考文獻 74
附錄 I
A.1台灣追蹤站GPS序列資料處理詳細成果 I
A.1.1 FLNM站 I
A.1.2 YMSM站 III
A.1.3 KDNM站 IV
A.1.4 KMNM站 V
A.1.5 MZUM站 VII
A.1.6 PKGM站 VIII
A.1.7 TMAM站 IX
A.2台灣追蹤站資料品質提升前之速度場估計 X
A.3台灣追蹤站資料品質提升後之速度場估計 XV
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