Abstract:The outer surface of large remote sensing satellites consists of polyhedral structure. The overlap rate between images of adjacent surfaces are very low and the orientation target is visible in just a few images. As a result, it is difficult to orient the whole photogrammetric image network. The measurement accuracy of such structure is low. A photogrammetric network orientation method for large threedimensional (3D) structures is proposed. The relative exterior orientation parameters between images are solved by the 5point method using several coded targets. Then, a relative orientation link is built and extended to involve all the images by maximizing the number of coded targets. In this way, the backprojection error is minimized, and the global relative orientation of the photogrammetric image network of large 3D structures is realized. The method is applied to photogrammetric measurement of the out surface of a 35 m×35 m×22 m remote sensing satellite. Results show that the orientation completion and accuracy of the method are better than those of the traditional methods. The method provides accurate and reliable initial estimation of exterior parameters for the photogrammetric images of large spacecraft components with 3D structures. The standard deviation of exterior angle parameters is smaller than 0000 3 rad, and the standard deviation of translation parameters is smaller than 07 mm.