GIS的非线性测量数据的误差处理及其应用

Application of processing error of nonlinear surveying and mapping data based on GIS

针对GIS数据应用中所存在的随机误差处理这一重要问题,本文提出了一种非线性最小二乘条件平差方法,给出了顾及泰勒二阶展开的基于空间数据随机误差的非线性条件平差模型,并结合算例将该方法与线性最小二乘平差方法加以比较,结果表明,当观测值与其平差值相近时,应用非线性最小二乘条件平差可明显提高平差结果的精度,这对于解决数字化处理过程中,因源文件中图形间的相互作用而引入大量误差,从而导致不能将非线性条件方程直接线性化问题提供了一种新的方法。

In view of the important problem of the random errors of GIS data processing, nonlinear least square is put forward and the model of nonlinear least square based on space data random errors from 2 order thaler is introduced. From some examples ,when observations and adjusted data are near, the precision is more higher using nonlinear least square than using linear least square .The errors from the pictures interactions of the original files in the course of digital processing will bring a problem that nonlinear equations is not linearized straight .And a new method will be introduced to solve this problem in this paper.