Abstract
Usually, the rational polynomial coefficient (RPC) model of spaceborne synthetic aperture radar (SAR) is fitted by the original range Doppler (RD) model. However, the radar signal is affected by two-way atmospheric delay, which causes measurement error in the slant range term of the RD model. In this paper, two atmospheric delay correction methods are proposed for use in terrain-independent RPC fitting: single-scene SAR imaging with a unique atmospheric delay correction parameter (plan 1) and single-scene SAR imaging with spatially varying atmospheric delay correction parameters (plan 2). The feasibility of the two methods was verified by conducting fitting experiments and geometric positioning accuracy verification of the RPC model. The experiments for the GF-3 satellite were performed by using global meteorological data, a global digital elevation model, and ground control data from several regions in China. The experimental results show that it is feasible to use plan 1 or plan 2 to correct the atmospheric delay error, no matter whether in plain, mountainous, or plateau areas. Moreover, the geometric positioning accuracy of the RPC model after correcting the atmospheric delay was improved to better than 3 m. This is of great significance for the efficient and high-precision geometric processing of spaceborne SAR images.
Highlights
Since 1999, for the IKONOS satellite, considering technical confidentiality and other factors, American space imaging companies have started to provide rational polynomial coefficient (RPC)models instead of rigorous geometry models to end users as basic imaging products [1]
Based on the range Doppler (RD) model, this paper describes a method of fitting the RPC model of a spaceborne
For the RPC model fitted using the original RD model without atmospheric delay correction, positioning accuracy verification was conducted; After correcting the systematic error in the slant range direction of the GF-3 synthetic aperture radar (SAR) satellite, geometric positioning accuracy verification of the RPC model was performed. This systematic error was obtained by geometric calibration of the spaceborne SAR [23]; After correcting the systematic error in the slant range direction of the GF-3 SAR satellite and correcting the atmospheric propagation delay error using plan 1, geometric positioning accuracy verification of the RPC model was performed; After correcting the systematic error in the slant range direction of the GF-3 SAR satellite and correcting the atmospheric propagation delay error using plan 2, geometric positioning accuracy verification of the RPC model was performed
Summary
Since 1999, for the IKONOS satellite, considering technical confidentiality and other factors, American space imaging companies have started to provide rational polynomial coefficient (RPC)models instead of rigorous geometry models to end users as basic imaging products [1]. The RPC model is a universal geometric model of remote sensing satellite sensors, which is usually fitted by a range. With the emergence of various imaging sensors, it is difficult for end users to add new sensor models to existing software systems to process new sensor data, while the RPC model solves this difficulty well. Sensors 2020, 20, 553 the multi-source sensor data application, the RPC model provides a unified geometric model for the joint adjustment of multi-source, high-resolution remote sensing images. In view of these characteristics and factors, the RPC model has been widely used in photogrammetric processing of remote sensing satellite images
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