摘要
构造了加权整体最小二乘EIO(errors-in-observations)模型,只改正独立观测值,观测值协因数阵最简洁,可克服EIV模型缺陷。基于EIO模型推导了参数估计和协因数阵精确迭代算法,实例结果正确,计算效率高。
EIO (errors-in-observations) model is proposed for the weighted total least squares adjustment problem.The EIO model only corrects the independent observations.The observation cofactor matrix has the simplest structure.The flaw of EIV model is overcome.Based on the EIO model,the precise parameter estimation and cofactor matrix formulations are derived and proved by several examples,which show that the results are correct and the algorithm is efficient.
作者
邓兴升
彭思淳
游扬声
DENG Xingsheng;PENG Sichun;YOU Yangsheng(School of Traffic and Transportation Engineering,Changsha University of Science & Technology,Changsha 410114,China;School of Civil Engineering,Chongqing University,Chongqing 400044,China)
出处
《测绘学报》
EI
CSCD
北大核心
2019年第7期926-930,共5页
Acta Geodaetica et Cartographica Sinica
基金
国家自然科学基金(41671498)
公路地质灾变预警空间信息技术湖南省工程实验室基金(KFJ150602)~~
关键词
加权整体最小二乘
EIO模型
参数估计
协因数阵
迭代算法
weight total least square (WTLS)
errors-in-observations (EIO) model
parameter estimation
cofactor matrix
iterative algorithm
