摘要
测量平差与数据处理所涉及到的误差模型大多为非线性模型。对非线性模型作线性化处理必然导致信息的损失和特征的改变。因此 ,在非线性模型空间内进行测量平差与数据处理是学科发展的必然趋势。在对非线性函数误差模型与非线性随机误差模型作出假定的基础上 ,本文着重讨论了关系型函数模型与相关型函数模型中参数的估计准则与解算方法。
Most error models about surveying adjustment and data processing are of nonlinear. Linearization of non linear models always leads to losses of information and alteration of characteristic. That doing some surveying adjustment and data analysis within nonlinear model fields is an inevitable trend of development of surveying and mapping branch. In this paper, based on hypothesis of nonlinear function error model and random error models, the estimation are guides discussed mainly and methods on paramaters in relational function models and related function models.
出处
《测绘工程》
CSCD
2000年第3期19-22,共4页
Engineering of Surveying and Mapping
基金
国家自然科学基金资助项目!(497742 0 9)
湖南省自然科学基金资助项目!(970 44)
关键词
非线性模型
参数估计
最速下降法
测量平差
Nonlinear models
Paramaters estimation
Least absolute sum
Steepest descend method
Nonlinear optimization
