Accuracy Analysis of Spaceborne Heterologous Multi-view Stereo Positioning with SAR Image Substitute of CCD Image

  • Ying-ying Li
  • Hao Wu
  • En Long
  • Xueli Chang
  • Zhixin Li
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 499)


Data source access conditions of traditional homologous CCD stereo are very harsh. With the greatly improvement of spaceborne SAR image resolution, in particular its all-time all-weather observation capability and height sensitive side-view feature, SAR has become an effective complement to optical remote sensing, thereby which greatly increase the possibility of stereo conformation. And heterologous stereo precision is expected to reach or exceed the homologous optical stereo. However, because its data source is not uniform and precision factors are multiple, a comprehensive error analysis law should be put forward to support if the heterologous stereoscopic would be put into application. But current studies could not present clear conclusion. In this article, first the equivalent relationship between SAR strict geometry model and the rational polynomial model (RPC) is derived. Through the whole link error propagation modeling, we simulate and evaluate the quantitative relationship between the positioning accuracy and influencing factors such as the source image angle, corresponding points matching accuracy. Then the theoretical accuracy and superiority achieved by heterogeneous stereoscopic can be analyzed. In-orbit data tests are conducted to fully verify our theory correctness, and the error rules under different data combinations are detailed analyzed, which will provide a reliable basis for the heterologous practical applications.


Heterologous multi-view Stereo positioning Rational polynomial model (RPC) Error propagation 



This work was supported by the National Natural Science Foundation of China (Project No. 61501036) and the Opening Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences (LSU-2016-06-01).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Ying-ying Li
    • 1
  • Hao Wu
    • 1
  • En Long
    • 1
  • Xueli Chang
    • 2
  • Zhixin Li
    • 1
  1. 1.Institute of Remote Sensing Information of BeijingHaidian, BeijingChina
  2. 2.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityWuhanChina

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