【摘要】：聯合多種特征進行攝影測量平差不僅可以減少對特征點的依賴性,而且可以增加冗余,增強攝影測量平差的幾何穩(wěn)定性,從而提高解算精度。但目前的多特征幾何定位模型存在以下幾個問題:(1)將空間坐標變換分解為旋轉和平移兩部分,旋轉量通常采用歐拉角描述,旋轉量與平移量是分開求解的,這會造成旋轉平移在時域上的斷裂,引入耦合誤差。(2)平差形式與點攝影測量一致,沒有充分利用直線、曲線等特征的幾何拓撲關系。針對目前多特征幾何定位模型存在的問題,本文提出以螺旋運動為幾何基礎進行后方交會的全新理論和方法。在深入研究空間直線表達以及其空間拓撲關系數學描述的基礎上,建立基于螺旋運動的多特征后方交會幾何模型。分別將成像光線和控制直線用Plücker坐標表示,利用對偶四元數實現成像光線的螺旋運動,根據成像幾何原理,對點特征建立基于螺旋運動的共線條件方程,對直線特征建立基于螺旋運動的共面條件方程,點線聯合平差實現了位置參數與姿態(tài)參數的一體化解算。實驗表明,本文提出的方法針對模擬影像、加入高斯白噪聲的模擬影像和實際影像均能夠獲得正確、穩(wěn)定的定位結果,相比于傳統(tǒng)的空間后方交會方法,能獲得更高的精度,此外,它還克服了傳統(tǒng)后方交會方法像方和物方需要同名點的缺陷。本文研究成果為城區(qū)等直線特征豐富地區(qū)的影像后方交會提供了一種新思路。
[Abstract]:The photogrammetric adjustment combined with multiple features can not only reduce the dependence on the feature points but also increase the redundancy and enhance the geometric stability of the photogrammetric adjustment thus improving the accuracy of the solution. However, there are several problems in the present multi-feature geometric localization model: (1) the spatial coordinate transformation is decomposed into two parts: rotation and translation. The rotation is usually described by Euler angle, and the rotation and translation are solved separately. This will result in the fracture of rotation translation in time domain, and introduce coupling error. (2) the adjustment form is consistent with the point photogrammetry and does not make full use of the geometric and topological relations of the characteristics such as lines and curves. In view of the problems existing in the current multi-feature geometric positioning model, a new theory and method of rear intersection based on spiral motion is proposed in this paper. Based on the deep study of the spatial straight line representation and the mathematical description of the spatial topological relationship, a multi-feature rear intersection geometric model based on spiral motion is established. The imaging ray and the control line are represented by Pl 眉 cker coordinates, and the spiral motion of the imaging light is realized by using dual quaternion. According to the principle of imaging geometry, the collinear condition equation based on helical motion is established according to the principle of imaging geometry. The coplanar condition equation based on helical motion is established for the linear features and the integration of position and attitude parameters is realized by the combination of point and line adjustment. The experimental results show that the proposed method can obtain correct and stable positioning results by adding Gao Si white noise to the simulated image and the actual image. Compared with the traditional space rear rendezvous method, the proposed method can achieve higher accuracy. In addition, it overcomes the defect that the traditional rear-area rendezvous method needs the same point. The results of this paper provide a new idea for the image rear intersection in the urban areas with abundant linear features.
【學位授予單位】：南京航空航天大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：P23;P207

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