Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/7721
標題: 以簡單目標估測法為輔的多重影像座標萃取技術於目標定位之研究
Simple Target Estimation-Based Multiple Image Coordinate Extraction Technique for Target Positioning
作者: 陳文斌
Chen, Win-Bin
關鍵字: 簡單目標估測;simple target estimation (STE);多重影像座標萃取;以方向為目的插入遺失線的解交錯演算法;multiple image coordinate extraction (MICE);de-interlacing technique on the basis of direction-oriented interpolation
出版社: 電機工程學系所
引用: [1] Thomas B. Criss, Marilyn M. South (1998), “Multiple Image Coordinate Extraction (MICE) Technique for Rapid Targeting of Precision Guided Munitions”, JOHNS HOPKINS APL TECHNICAL DIGEST, VOL. 19, No. 4 [2] Hoon Yoo and Jechang Jeong, “Direction-oriented interpolation and its application to de-interlacing”, IEEE Trans.Consumer Electronics,vol 48,Issue 4,pp.954-962,Nov.2003. [3] T. F. Coleman, Y. Li, “An Interior, Trust Region Approach for Nonlinear Minimization Subject to Bounds”, SIAM Journal on Optimization, Vol. 6, pp. 418-445, 1996. [4] T. F. Coleman, Y. Li, “On the Convergence of Reflective Newton Methods for Large-Scale Nonlinear Minimization Subject to Bounds”, Mathematical Programming, Vol. 67, Number 2, pp. 189-224, 1994. [5] Arthur Gelb, Joseph F. Kasper, Jr., Raymond A. Nash, Jr., Charles F. Price, Arthur A. Sutherland, Jr., “Applied Optimal Estimation”, The M.I.T. Press. [6] Levenberg, K., “A Method for the Solution of Certain Problems in Least-Squares,” Quarterly Applied Math. 2, pp. 164-168, 1944. [7] Marquardt, D., “An Algorithm for Least-Squares Estimation of Nonlinear Parameters,” SIAM Journal Applied Math., Vol. 11, pp. 431-441, 1963. [8] J. J. More, “The Levenberg-Marquardt Algorithm: Implementation and Theory,” Numerical Analysis, ed. G. A. Watson, Lecture Notes in Mathematics 630, Springer Verlag, pp. 105-116, 1977. [9] R. H. Byrd , R. B. Schnabel, “Approximate solution for the trust region problem by minimization over two-dimensional subspaces,” Mathematical Programming, 40(1998), pp. 247-263. [10]T. F. Coleman, C. Hempel, “Computing a trust region step for a penalty function,” SIAM Journal on Scientific and Statistical Computing, 11(1990), pp. 180-201. [11]T. F. Coleman, L. A. Hulbert, “A direct active set algorithm for large sparse quadratic programs with simple bounds,” Mathematical Programming, 45(1989), pp.373-406. [12]T. F. Coleman, Y. Li, “On the convergence of reflective Newton methods for large-scale nonlinear minimization subject to bounds,” Tech.Rep.TR 92-1314, Computer Science Department, Cormell University,1992. [13]A. R. Conn, N. I. M. Gould, P. L. Toint, “Global convergence of a class of trust region algorithms for optimization with simple bounds,” SIAM Journal on Numerical Analysis,25(1998),pp.433-460. [14] R. S. Dembo, U. Tulowttzki, “On the minimization of quadratic functions subject to box constraints,” Tech.Rep.B 71,Yale University, 1983. [15]R. Fletcher , M. P. Jackson, “Minimization of a quadratic function of many variables subject only to lower and upper bounds,” Journal of the Institute for Mathematics and its Applications, 14(1974), pp.159-174. [16]D. M. Gay, “Computing optimal locally constrained steps,” SIAM Journal on Scientific and Statistical Computing,2(1982),pp.186-197. [17]P. Gill, W.Murray, “Minimization subject to bounds on the variables,” Tech. Rep. Report NAC 71, National Physical Laboratory, England, 1976. [18]P. Lotstedt, “Solving the minimal least squares problem subject to bounds on the variables,” BIT,24(1984),pp.206-224. [19]J. J. More, “Recent developments in algorithms and software for trust region methods, in Mathematical Programming: The State of the Art,” M.G. A. Bachem and e. B. Dorte. eds., Springer Verlag, Berlin, 1983. [20]J. J. More, D. Sorensen, “Computing a trust region step,” SIAM Journal on Scientific and Statistical Computing, 4(1983), pp. 553-572. [21]J. J. More, G.Toraldo, “Algorithms for bound constrained quadratic programming problems,” Numerische Mathematik, 55(1989), pp. 377-400. [22]D. P. O’Leary, “A generalized conjugate gradient algorithm for solving a class of quadratic programming problems,” Linear Algebra and its Applications, 34 (1980), pp. 371-399. [23]U. Oreborn, “A direct method for sparse nonnegative least squares problems,” PhD thesis, Department of Mathematics, Linkoping University, Linkoping, Sweden, 1986. [24]G. A. Schultz, R. B. Schnabel, R.H.Byrd, “A family of trust-region- based algorithms for unconstrained minimization with strong global convergence properties,” SIAM Journal on Numerical Analysis, 22(1) (1985), pp. 47-67. [25]劉世壹, 多影像三維座標重建系統實作, 國立中興大學電機系, 2006 [26]TAU CORPORATION, ”Data Reduction Video Tracker Operator’s Manual”, 1992 [27]Matlab,Optimization Toolbox
摘要: 
本文提出一套以簡單目標估測(Simple Target Estimation,STE)演算法為輔的多重影像座標萃取(Multiple Image Coordinate Extraction,MICE)技術,用以快速且精確的計算出目標位置。
在本方法中,我們使用一套飛行載具模擬軟體,模擬飛行載具在3D環境中飛經目標區域,紀錄下多張目標的影像,同時也紀錄每張影像所對應的飛行載具位置數據,然後應用MICE技術執行目標定位。
在進行目標定位估算時,MICE估測演算法很難求得最佳解,必經由多次嘗試錯誤法方能求得最佳解,因此,限制了MICE的應用性。在本文中,我們首先應用STE,求取目標的粗略位置,用以限定求解範圍,於是應用MICE技術便可快速估算出目標的精確位置。
在本文中,我們也介紹以方向為目標的插入遺失線解交錯演算法,用以抑制交錯影像對目標定位的影響。此外,我們也將介紹在實務上應用廣泛的低密度大地高程資料轉換為高密度大地高程資料的概念。
藉由本文的實驗,我們證實了STE確實可以有效地輔助MICE技術獲得精確的目標定位。

This thesis proposes a quick and precise method for target positioning using multiple image coordinate extraction (MICE) technique based on the simple target estimation (STE).
In this approach, an aerial vehicle cruises through the target area in a simulated 3D graphic scenario, taking multiple images of the target. Then the obtained images and the associated aerial vehicle's position data are recorded. After that, the MICE technique is performed to extract the target coordinates.
It is hard to get the global solution using the MICE technique to estimate target positions. Generally, the solution can be achieved by a method of try and error with lots of time. In this thesis, the boundaries of solutions are first limited by the STE technique, which estimates the target positions approximately. Then, the MICE approach can speed up the estimation of the target coordinates precisely.
In this thesis, a de-interlacing technique on the basis of direction-oriented interpolation is introduced. It is used to suppress the effect of the interlaced images on the target positioning. In addition, a concept on high density terrain data transformed from low density terrain data is made.
Experimental results demonstrate that the STE approach can effectively speed up the MICE technique in precise estimation of target positioning.
URI: http://hdl.handle.net/11455/7721
其他識別: U0005-2601200811381100
Appears in Collections:電機工程學系所

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