光学卫星遥感影像的RFM迭代平差方法

The RFM Iterative Adjustment Method for Optical Satellite Remote Sensing Imagery

有理函数模型(Rational Function Model,RFM)作为光学卫星遥感影像几何处理的一种主要模型,其平差方法一直是卫星摄影测量研究的重点。文章在常规的像方平差方案基础上提出RFM迭代平差方法,先用仿射变换多项式消除内外方位元素引起的像方定位误差,再连续使用傅里叶多项式逐步消除影像复杂畸变,通过两者结合提升对影像系统误差的综合补偿能力。通过对ZY-3和GF-7两种国产卫星遥感影像进行实验,结果显示:RFM定位精度随迭代平差次数的增加而提高,经过3次平差后中误差逐渐收敛。相比一次平差结果,迭代平差后ZY-3影像的平面和高程定位中误差降低了8%和13%,GF-7影像的平面和高程定位中误差降低了12%和30%,所生成的RPC参数可更好地满足高精度定位需求。

The RFM model for optical satellite remote sensing images is a major model for geometric processing of optical satellite remote sensing images,and its adjustment method has always been a focus of satellite photogrammetry research.This article proposes an RFM iterative adjustment method based on the image space adjustment solution.Firstly,affine transformation polynomials are used to eliminate the image positioning error caused by internal and external orientation elements.Then,Fourier polynomials are continuously used to gradually eliminate complex image distortions.By combining both polynomials,the comprehensive compensation ability for eliminating image system errors is improved.The experimental results on two domestic satellite remote sensing images,ZY-3 and GF-7,show that the RFM positioning accuracy improves with the increase of iteration adjustment times,and the RMSE gradually converges after three times.Compared to the results of common adjustment solution,after iterative adjustment the RMSE of the plane and elevation positioning of ZY-3 images decreased by 8%and 13%,and the RMSE of the plane and elevation positioning of GF-7 images decreased by 12%and 30%.The RPC parameters generated after iterative adjustment can better meet the high-precision positioning requirements.