Differential sensitivity analysis for the orthorectification of small satellite images

O. Bettemir
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引用次数: 5

Abstract

By using differential sensitivity analysis, horizontal and vertical accuracy of orthorectification of monoscopic images taken by small satellites without using Ground Control Points (GCP) is predicted. The analysis is performed by differentiating the colinearity equation of orthorectification procedure with respect to the satellite's interior and exterior parameters, and elevation obtained from digital elevation model (DEM). Square of the differential equations with respect to parameters are multiplied with the variance covariance matrix of the parameters and horizontal uncertainty of the orthorectification is obtained by summing the results of this multiplication. Vertical uncertainty is caused by the uncertainty of DEM and the uncertainty of the horizontal position. Vertical uncertainty caused by the horizontal uncertainty is predicted by estimating a trend by generating a surface polynomial from DEM on the basis of covariance function of Hirvonen. Contribution of each error source is illustrated and the most sensitive parameter is obtained. With this knowledge, special weight can be given to the most sensitive parameter and the uncertainty of the orthorectification can be decreased in the most efficient way.
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小卫星图像正校正的差分灵敏度分析
利用差分灵敏度分析方法,预测了不使用地面控制点(GCP)的小卫星单镜影像正校正的水平和垂直精度。通过对正校正过程对卫星内外参数和数字高程模型(DEM)获得的高程的共线性方程求导进行分析。将微分方程关于参数的平方与参数的方差协方差矩阵相乘,并将相乘结果相加得到正校正的水平不确定度。垂直不确定性是由DEM的不确定性和水平位置的不确定性引起的。在Hirvonen协方差函数的基础上,通过从DEM中生成曲面多项式估计趋势来预测水平不确定性引起的垂直不确定性。说明了各误差源的贡献,得到了最敏感的参数。有了这些知识,就可以对最敏感的参数赋予特殊的权重,从而以最有效的方式降低正校正的不确定性。
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