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DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 韓仁毓 | |
dc.contributor.author | Yi-Tzen Yueh | en |
dc.contributor.author | 樂怡岑 | zh_TW |
dc.date.accessioned | 2021-06-15T06:04:27Z | - |
dc.date.available | 2011-08-16 | |
dc.date.copyright | 2010-08-16 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-08-16 | |
dc.identifier.citation | Altamimi, Z., Sillard, P., and Boucher, C. (2002). “ITRF2000: A new release of the International Terrestrial Reference Frame for earth science application.” J. Geophys. Res., 107(B10), ETG2/1-19.
Arun,K.S., Huang,T.S., Blostein,S.D. (1987). “Least-squares fitting of two 3-D point sets.” IEEE Trans.PAMI, 9(5), pp. 698-700. Awange, J.L., and Grafarend, E.W. (2003). “Closed form solution of the overdetermined nonlinear 7 parameter datum transformation.” Allgemeine Vermessungs Nachrichten (AVN) 110, pp. 130-148. Awange, J.L., and Grafarend, E.W. (2005). Solving Algebraic Computational Problems in Geodesy and Geoinformatics, Springer, Berlin. Badekas, J. (1969). “Investigations Related to the Establishment of a World Geodetic System.” Report No. 124, Department of Geodetic Science, The Ohio State University, Columbus, OH. Billington, E. W. and Tate, A. (1981). The physics of deformation and flow / E. W. Billington and A. Tate McGraw-Hill International Book Co., New York ; London : Han, J.Y., and van Gelder, B.H.W (2006). “Stepwise parameter estimations for a time-variant similarity transformation.” J. Surv. Eng., 132(4), pp. 141-148. Han, J.Y. (2010) A non-iterative approach for solving the indirect problems of linear reference frame transformations, J. Surv. Eng., – ASCE, available online 5 Jan 2010, doi:10.1061/(ASCE)SU.1943-S428.0000026.. Jaw, J.J., and Chuang, T.Y. (2008). “Registration of ground based LIDAR point clouds by means of 3D line features” J.Chinese Inst. of Eng., 31(6), pp. 1031-1045. Leick, A., and van Gelder, B.H.W. (1975). “On similarity transformation and geodetic network distortions based on Doppler satellite observations.” Report No. 235, Department of Geodetic Science, The Ohio State University,Columbus, OH. Mikhail, E.M., and Ackermann, F. (1976). Observations and Least Squares. IEP-A Dun-Donnelley Publisher, New York. Mikhail, E.M., Bethel, J.S., and McGlone, J.C (2001). Introduction to Modern Photogrammetry. John Wiley &Sons, Inc., New York. Molodenskii, M.S., Eremeey, V.F., and Yurkina, M.I. (1962). “Methods for study of the external gravitational field and figure of the earth (transl. from Russian 1960).” National Technical Information Services, Springfield,VA. Rabbani, T., Dijkman, S., van den Heuvel, F., and Vosselman G. (2007). “An integrated approach for modeling and global registration of point clouds. ” ISPRS Journal of Photogrammetry & Remote Sensing, 61(6), pp. 355-370. Soler, T., and ven Gelder, B.H.W. (1987). “On differential scale changes and the satellite Doppler system Z-shift.” Geophys. J. R. Astr. Soc., 91(3), pp. 639-656. Soler, T., (1998). “A compendium of transformation formulas useful in GPS work.” J.Geod., 72(2-8), pp. 482-490. Soler, T., and Snay, R.A. (2004). “Transforming positions and velocities between the International Terrestrial Reference Frame of 2000 and North American Datum of 1983.” J. Surv. Eng., 130(2), pp. 49-55. van Gelder, B.H.W. (2003). Geodesy. In W.F. Chen and J.Y. Richard Liew(Eds.), The Civil Engineering Handbook. CPC Press, Boca Raton, FL, 55-1/68. von Hansen, W., Gross, H., and Thoennessen, U. (2008). “Line-based registration of terrestrial and aerial LIDAR data.” Int. Archives of the Photogrammetry, Remote Sensing, and Spatial Information Sciences, XXXVII part B3a, pp. 161-166. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/47529 | - |
dc.description.abstract | 不同參考坐標系統之間的轉換是應用空間資訊時常遇見的問題,其中由於線性轉換之型式較為簡易且所引進之參數具有明確之物理意義,在實務上常被廣泛使用,而相似轉換即屬線性轉換之一種,其傳統之求解方式乃是透過轉換前後之坐標值組成觀測量,以最小自乘法求得參數的最佳估值。然而利用最小自乘法求解時,會因為迭代而使解算效率降低,且參數求解時之起始值給定亦是一項問題,此外,於可及性較差之地區難以佈設控制點,若侷限於使用點位坐標作為觀測資訊,將增加轉換參數求解之困難。本研究主要目的為建立一相似轉換的非迭代解法(Non-iterative solution for Helmert Transformations, NIHT)之程序,以提升相似轉換模型參數之解算效率,並建立NIHT法的觀測量加權模式,使其能夠合理處理品質不一的觀測輸入資料,此外並建立轉換參數之精度估計模式。而此方法可延伸應用於使用非點狀之混合控制特徵進行轉換參數解算,因此可廣泛的應用於各類線性轉換問題中。在數值分析中,本研究除了透過模擬資料來驗證本研究方法之正確性,並且利用多測站光達掃瞄點雲套合作業作為應用範例,展示本研究方法於實際空間資訊分析工作之可行性。從實驗成果顯示,本研究所提之NIHT參數估計法可使得線性轉換參數解算過程更具彈性且合理可靠,因此對於空間資訊科學之相關應用工作將有具體助益。 | zh_TW |
dc.description.abstract | The Helmert transformation model is of a frequent choice for transforming coordinates between different reference frames due to the fact that it has simple and physically interpretable parameters. The indirect problem (i.e., the parameter estimations) of the Helmert transformation model is usually solved by applying the classical least-squares technique. However, an appropriate set of initial values and iterative computations are required during the parameter estimation process, and the computation may become very inefficient. Besides, only using point coordinates as observables for parameter estimations is very difficult if the target area isn’t reachable for setting control points. In this study, a non-iterative approach for solving the indirect problem of the Helmert Transformation model (NIHT) is proposed to improve the computational efficiency in estimating the transformation parameters, and then a weighted NIHT is developed to deal with the observables of varied levels of quality. Besides, the proposed method is further extended to make use of hybrid control features, including lines, planes and groups of dispersed point clouds. Based on the simulation test results, it is illustrated that the proposed approach is capable of giving a direct and quality parameter solution. Followed by a real case study in which LiDAR point clouds from multiple scanning stations were integrated, it was further concluded that the NIHT technique provides a flexible and reliable solution and will thus benefit related spatial science applications in which linear transformations are involved and to be analyzed. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T06:04:27Z (GMT). No. of bitstreams: 1 ntu-99-R97521109-1.pdf: 2107304 bytes, checksum: 7f787e1297858e541e96155b04577c7d (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | 目 錄
口試委員審定書……………… i 致謝……………….…………… ii 摘要..………………………… iii Abstract……………………… iv 目錄…...………….……….… v 圖目錄 .………………………… vii 表目錄 .…..…………………… ix 第一章 緒論…………………… 1 1.1研究背景…………………… 1 1.2研究動機…………………… 1 1.3相關研究…………………… 2 1.4研究目的與方法……………… 2 1.5論文架構……………………… 3 第二章 文獻回顧………………… 4 2.1相似轉換模型…………………… 5 2.2相似轉換的應用…………………… 5 2.3轉換參數求解方法……………… 6 2.3.1傳統最小自乘估計法…………… 6 2.3.2非迭代解法一: Non iterative Least Square Fitting……… 7 2.3.3非迭代解法二: Invariant Polynimials…………...…… 8 2.3.4非迭代解法三: Procrustean……...…...……………… 9 第三章 相似轉換之非迭代參數解算法……………… 12 3.1 NIHT方法介紹…………………………… 12 3.2加權模式………………………… 15 3.2.1尺度因子加權...…………… 15 3.2.2 旋轉矩陣加權...…………… 16 3.2.3平移量加權...…………… 16 3.2.4加權模式對參數估計所產生的影響…...…… 17 3.3參數精度估計………..……… 19 3.4多重特徵之轉換……..……… 23 3.4.1 線特徵………..………...… 23 3.4.2 面特徵………..………...… 24 3.4.3 離散點雲………..……...… 25 3.4.4 輔助特徵………..……...… 28 3.5 可解條件探討……...…..…… 28 3.5.1 點特徵……...…..……...… 29 3.5.2 線特徵……...…..……...… 29 3.5.3 面特徵……...…..……...… 30 3.5.4 離散點雲……...…..……... 31 3.5.5 混合特徵……...…..……... 32 3.5.6 本研究之非迭代解法可用之觀測量…………… 32 第四章 數值驗證與分析………………………… 35 4.1 模擬資料-以點特徵為觀測資訊求解轉換參數…………35 4.1.1 不考量觀測資訊精度-不加權進行求解…………..36 4.1.2 考量觀測資訊精度-加權求解…………...... 37 4.2模擬資料-以混合特徵為觀測資訊求解轉換參數…… 38 4.3 實例應用-多測站之離散光達點雲之整合………… 40 第五章 結論與建議…………………………… 48 5.1結論…………………………………………………48 5.2 建議與未來工作……………………50 參考文獻……………………………52 圖目錄 圖3-1不同框架下,對應之觀測量產生尺度變化 ……… 13 圖3-2不同點數,最小自乘法和NIHT求解所需時間……… 15 圖3-3觀測量精度不同時加權與否的解算成果 ………… 17 圖3-4加權對尺度參數之影響 .……………………… 18 圖3-5加權對三軸旋轉角之影響 …………………………… 18 圖3-6加權後對平移參數之影響 ………………………………19 圖3-7線特徵示意圖 ……………………………………… 23 圖3-8面特徵示意圖 …..…………………… 24 圖3-9長條狀物體於轉換前後之三軸特徵值與特徵向量示意圖 ………… 27 圖3-10面狀物體於轉換前後之三軸特徵值與特徵向量示意圖 ……… 27 圖3-11輔助特徵示意圖 ………………………………………………… 28 圖3-12由點特徵求解轉換參數之坐標向量差值示意圖 …………… 29 圖3-13由線特徵求解轉換參數之坐標向量差值示意圖 ……………… 30 圖3-14由面特徵求解轉換參數之坐標向量差值示意圖 …………… 31 圖3-15 NIHT法求解程序流程圖 .......................... 34 圖4-1點位隨機誤差為0.02m及0.5m之隨機分佈圖 …………………… 35 圖4-2 NIHT法求解之觀測量殘差向量圖以及三軸分佈圖-無加權 … 36 圖4-3 NIHT法求解之觀測量殘差向量圖以及三軸分佈圖-加權 …… 37 圖4-4模擬混合特徵於轉換前後框架 …………………………… 39 圖4-5測距長度相對之測量標準差…………………………… 41 圖4-6萬壽橋實驗場景(google earth之衛星影像圖) ………… 41 圖4-7測站S1之點雲分布 …………………………… 42 圖4-8測站S2之點雲分布 ……………………………… 42 圖4-9測站S1(a)及S2(b)選取點雲之特徵向量 ………… 43 圖4-10測站S1(a)和測站S2(b)之光達點雲 ………… 43 圖4-11不同視角之光達點雲套合成果(a)(b) ……… 44 圖4-11不同視角之光達點雲套合成果(c)(d) ……… 45 圖5-1航空攝影測量之共線式圖示………………...… 50 圖5-2地理資訊系統內圖層對應之坐標轉換示意圖……… 51 表目錄 表2-1坐標轉換方法比較 ……………………………… 11 表3-1 NIHT求解所需之觀測量 ……………………… 32 表3-2不同特徵之最小可解條件 .…………………… 33 表4-1同一群點位不同隨機誤差之求解結果-無加權 …… 36 表4-2同一群點位不同隨機誤差之求解結果-加權 ……… 37 表4-3觀測量為混合特徵求解轉換參數 …………… 39 表4-4混合特徵求解之轉換參數估值 ….....……… 39 表4-5雷射掃描儀之規格表 …………… 40 表4-6檢核點之估計誤差與實際精度 ….....… 46 表4-7利用控制球求解轉換參數之殘差 .....…… 46 | |
dc.language.iso | zh-TW | |
dc.title | 相似轉換之非迭代參數估計法 | zh_TW |
dc.title | A Non-Iterative Approach for Solving the Parameters of a Helmert Transformation | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 史天元(Tian-Yuan Shih),詹進發,趙鍵哲 | |
dc.subject.keyword | 相似轉換,坐標框架轉換,參數求解,非迭代線性轉換參數估計, | zh_TW |
dc.subject.keyword | Helmert Transformations,Frame Transformations,Parameter Estimations,Non-Iterative Solution for Linear Transformations, | en |
dc.relation.page | 53 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2010-08-16 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
顯示於系所單位: | 土木工程學系 |
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