Abstract
Abstract. High-precision satellite image geolocation is the basis for advanced processing of satellite image data. Aiming at the optimization of the satellite image positioning accuracy based on rational polynomial coefficients (RPC), we propose an RPC image-space bias model that combines object-space information. Based on a comprehensive analysis of the full-link error of the satellite image geometric imaging process, the real object coordinates are introduced into the RPC correction to make the bias model better fit the actual error. Experiments were performed using several image datasets from the Chinese satellite TianHui-1 (TH-1) and compared with the traditional RPC bias model. The results show that our model has strong robustness and can better correct image positioning errors. Compared with traditional bias models, it can improve the accuracy of plane positioning by approximately 1 pixel.
Highlights
In the past decade, high-resolution remote sensing satellites have been comprehensively developed and widely used
In the later stages of satellite data processing, controlled or uncontrolled regional bundle adjustment can generally be performed with a satellite rational function model (RFM) to improve the direct positioning accuracy or the consistency of the overall accuracy of satellite images
This paper focuses on the optimization of the satellite image positioning accuracy based on an rational polynomial coefficients (RPC) bias model
Summary
High-resolution remote sensing satellites have been comprehensively developed and widely used. All sensor models include orbit measurement errors, offset errors caused by attitude measurement errors, and image distortion errors (Cao et al, 2019) Most of these errors have been calibrated in the laboratory, due to the influence of the thermal and mechanical environment during satellite launch and operation, there is a certain deviation between the laboratory calibration values and the true values, and the direct positioning accuracy of satellite images cannot meet the target requirements. In the early stage of satellite data processing, the strict geometric imaging model of satellites and high-precision ground control points (GCPs) can generally be used to accurately calibrate the interior and exterior orientation elements of the satellite to improve the direct positioning accuracy of satellite images. When the affine transformation model cannot simulate the satellite on-orbit geometric calibration residuals well, the
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
