论文标题
空间探索的绝对三角算法
Absolute Triangulation Algorithms for Space Exploration
论文作者
论文摘要
图像是航天器导航和观察到的空间对象的三维重建的重要信息来源。当相机具有已知态度并且从图像中提取的测量值是视线（LOS）方向时，这两种应用都采用三角剖分问题的形式。这项工作对三角剖分的历史和理论基础进行了全面的综述。回顾了多种经典三角算法，包括许多次优线性方法（许多LOS测量）和Hartley和Sturm的最佳方法（只有两个LOS测量值）。结果表明，使用新的线性最佳正弦三角剖分（丢失）方法，可以在没有迭代作为线性系统的情况下解决最佳的多测量情况。在仅进行两次测量的情况下，Hartley和Sturm的丢失和多项式方法都提供了相同的结果。通过一些数值示例评估了各种三角测量算法，包括行星地形相对导航，天王星的仅角度光学导航，巴黎圣母院的3-D重建以及仅角度的相对导航。
Images are an important source of information for spacecraft navigation and for three-dimensional reconstruction of observed space objects. Both of these applications take the form of a triangulation problem when the camera has a known attitude and the measurements extracted from the image are line of sight (LOS) directions. This work provides a comprehensive review of the history and theoretical foundations of triangulation. A variety of classical triangulation algorithms are reviewed, including a number of suboptimal linear methods (many LOS measurements) and the optimal method of Hartley and Sturm (only two LOS measurements). It is shown that the optimal many-measurement case may be solved without iteration as a linear system using the new Linear Optimal Sine Triangulation (LOST) method. Both LOST and the polynomial method of Hartley and Sturm provide the same result in the case of only two measurements. The various triangulation algorithms are assessed with a few numerical examples, including planetary terrain relative navigation, angles-only optical navigation at Uranus, 3-D reconstruction of Notre-Dame de Paris, and angles-only relative navigation.
