Abstract
Generally, the classic three-dimensional (3D) geometric positioning of optical satellite imagery uses the least squares principle to calculate the coordinates of a ground point by minimizing the sum of the squares of the distances between two imaging rays, which requires the standard stereo data with good imaging geometric conditions. As for unconventional stereo images, the undesirable and ubiquitous weak intersection phenomena exist in data will lead to bad results or even calculation failures for the conventional method. By selecting the highest precision intersection point in block adjustment, a new method that can solve the 3D coordinates with higher accuracy and stability was proposed. Tests of two data sets covering different landscapes validated the effectiveness of the method. The results showed that the geo-positioning performance and robustness of the proposed method was better than that of the conventional method, and this advantage is even greater in areas with more undulating terrain and more images with weak convergence.
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