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研究生(外文):Hsiao-Fan Lin
論文名稱(外文):Derivation of Three-Dimensional Surface Displacement Field from the Integration of DInSAR and GNSS Data by Gibbs Random Fields
指導教授(外文):Jen-Yu Han
口試委員(外文):Chung-Yen KuoKuo-Hsin TsengKuo-En Ching
外文關鍵詞:Differential Interferometric Synthetic Aperture Radar (DInSAR)Global Navigation Satellite System (GNSS)3D Deformation AnalysisGibbs Random FieldData Fusion
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Driven by rapid progress in spatial information science, developing an efficient and low-cost 3D spatial data acquisition technique is becoming a key issue. Differential Interferometric Synthetic Aperture Radar (DInSAR) is capable of capturing detailed displacement signals of ground surface of a wide area. However, the line-of-sight (LOS) displacements derived from the DInSAR technique do not provide an accurate representation of the actual 3D deformation field. In this study, multiple sets of SAR images will be used to derive the LOS displacements time series. The 3D observations from the Global Navigation Satellite System (GNSS) technique will be used to provide highly accurate spatial constraints as boundary conditions to adjust LOS displacements by preserving the gradient field of LOS displacements. Finally, probability theory and Gibbs random field will be introduced to integrate all available information and a complete approach for delivering 3D displacement of ground surface will then be established. The experimental results show that despite the insufficient interferograms, the 3D displacement can be resolved by this construction methodology with higher accuracy than least square method. A reliable observation and analysis solution with a high accuracy and good coverage will then become available for the deformation monitoring tasks.
致謝 i
摘要 ii
目錄 iv
圖目錄 vii
表目錄 x
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 3
1.3 研究流程 4
1.4 論文架構 4
第二章 文獻回顧 5
2.1 地表變位之相關研究 5
2.1.1 地表變位之應用 5
2.1.2 地表變位分析方法 7
2.2 全球衛星導航系統與地表變位分析 8
2.2.1 全球衛星導航系統原理 8
2.2.2 全球衛星導航系統特性與地表變位分析 10
2.3 合成孔徑雷達干涉技術 11
2.3.1 合成孔徑雷達干涉技術原理 11
2.3.2 應用差分干涉技術於監測地表變位 13
2.4 整合GNSS和InSAR資料進行地表三維變位回復 14
2.4.1 GNSS和InSAR資料整合分析 14
2.4.2 回復地表三維變位之方法研究 15
2.5 小結 17
第三章 研究方法 18
3.1 以DInSAR技術進行LOS方向變位量解算 19
3.1.1 影像套合 19
3.1.2 干涉圖產製 20
3.1.3 地形效應移除 21
3.1.4 相位濾波 22
3.1.5 全相位回復 23
3.1.6 相位轉換變位 24
3.1.7 地形對位校正 24
3.2 GNSS資料處理 25
3.3 隨機場機率模型 27
3.3.1 影像不足而無法完整回復三維變位的逆問題 27
3.3.2 隨機場理論與貝式推論 27
3.3.3 馬可夫隨機場 28
3.3.4 吉布斯隨機場 29
3.4 DInSAR與GNSS資料之改正和整合 30
3.4.1 單一時間之LOS變位量改正 32
3.4.2 單一測站之LOS變位量時間序列擬合 33
3.4.3 地表三維變位隨機場模型建立 33
3.5 小結 35
第四章 實驗成果與分析 36
4.1 資料來源與分析 36
4.1.1 SAR影像資訊與來源 36
4.1.2 GNSS資料來源與處理 39
4.2 模擬實驗驗證 42
4.3 實際資料應用與分析 43
4.3.1 單一時間之LOS變位量改正 44
4.3.2 單一測站之LOS變位量時間序列擬合 51
4.3.3 區域三維變位場建構 53
4.4 成果評估與分析 59
第五章 結論與建議 61
5.1 結論 61
5.2 建議與未來工作 62
參考文獻 64
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