一种基于复共线性分析的RPC参数优选法  

An Optimized Method for Selecting Rational Polynomial Coefficients Based on Multicollinearity Analysis

作　　者：袁修孝[1] 曹金山[1] 

机构地区：[1]武汉大学遥感信息工程学院,武汉市珞喻路129号430079

出　　处：《武汉大学学报（信息科学版）》2011年第6期665-669,共5页Geomatics and Information Science of Wuhan University

基　　金：国家973计划资助项目(2006CB701302);国家创新研究群体科学基金资助项目(40721001)

摘　　要：推导了求解有理多项式系数（RPC）的严密误差方程,从分析误差方程设计矩阵列向量间的复共线性着手,提出了一种去相关的RPC参数优选方法。对一景SPOT-5 HRG 1A级影像进行实验,结果表明,当地面控制点稀疏时,通过优选20-30个RPC参数,可以很好地消除参数间的相关性,有效消除有理函数模型（RFM）在地形拟合中出现的振荡现象,可明显提高RPC参数求解和RFM的影像几何处理精度。当地面控制点足够多时,利用此方法优选的RPC参数进行地形拟合的结果与用常规最小二乘法求解的78个RPC参数实施地形拟合的结果完全一致。In the geometric processing of high-resolution satellite imagery,the general rational function model（RFM） consists of 78 rational polynomial coefficients（RPCs）,and the correlation between these coefficients will result in difficulties and accuracy degradation in solving the RPC.The rigorous error equations for solving the RPCs are derived,and an optimized method of selecting the RPCs by analyzing the multicollinearity between column vectors of the design matrix is proposed.A SPOT-5 HRG image in level 1A is selected and used.The empirical results have shown that selecting 20 to 30 RPCs could effectively eliminate the correlation between the coefficients,remove the oscillation in approximating the terrain by using the RFM,and obviously raise the solution accuracy of the RPCs and geometric processing accuracy based on the RFM with less ground control points（GCPs） available.When the GCPs are sufficient,the selected RPCs could acquire a consistent geometric accuracy in approximating the terrain with the 78 RPCs solved by the traditional least-squares method.

关 键 词：有理函数模型 有理多项式系数 复共线性分析 RPC参数选择 精度 

分 类 号：P237.3[天文地球—摄影测量与遥感] P231.4[天文地球—测绘科学与技术]