基于螺旋运动的多特征后方交会研究

发布时间：2018-10-31 12:25

【摘要】：联合多种特征进行摄影测量平差不仅可以减少对特征点的依赖性,而且可以增加冗余,增强摄影测量平差的几何稳定性,从而提高解算精度。但目前的多特征几何定位模型存在以下几个问题:(1)将空间坐标变换分解为旋转和平移两部分,旋转量通常采用欧拉角描述,旋转量与平移量是分开求解的,这会造成旋转平移在时域上的断裂,引入耦合误差。(2)平差形式与点摄影测量一致,没有充分利用直线、曲线等特征的几何拓扑关系。针对目前多特征几何定位模型存在的问题,本文提出以螺旋运动为几何基础进行后方交会的全新理论和方法。在深入研究空间直线表达以及其空间拓扑关系数学描述的基础上,建立基于螺旋运动的多特征后方交会几何模型。分别将成像光线和控制直线用Plücker坐标表示,利用对偶四元数实现成像光线的螺旋运动,根据成像几何原理,对点特征建立基于螺旋运动的共线条件方程,对直线特征建立基于螺旋运动的共面条件方程,点线联合平差实现了位置参数与姿态参数的一体化解算。实验表明,本文提出的方法针对模拟影像、加入高斯白噪声的模拟影像和实际影像均能够获得正确、稳定的定位结果,相比于传统的空间后方交会方法,能获得更高的精度,此外,它还克服了传统后方交会方法像方和物方需要同名点的缺陷。本文研究成果为城区等直线特征丰富地区的影像后方交会提供了一种新思路。
[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.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P23;P207

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