| 加权整体最小二乘EIO模型与算法 |
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| 引用本文： | 邓兴升,彭思淳,游扬声.加权整体最小二乘EIO模型与算法[J].测绘学报,2019,48(7):926-930. |
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| 作者姓名： | 邓兴升 彭思淳 游扬声 |
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| 作者单位： | 长沙理工大学交通运输工程学院,湖南 长沙,410114;重庆大学土木工程学院,重庆,400044 |
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| 基金项目： | 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） |
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| 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。
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| 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 |
| 收稿时间： | 2017-01-12 |
| 修稿时间： | 2017-05-10 |
Weighted total least square adjustment EIO model and its algorithms |
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| DENG Xingsheng,PENG Sichun,YOU Yangsheng.Weighted total least square adjustment EIO model and its algorithms[J].Acta Geodaetica et Cartographica Sinica,2019,48(7):926-930. |
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| Authors: | DENG Xingsheng PENG Sichun YOU Yangsheng |
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| Institution: | 1. School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China;2. School of Civil Engineering, Chongqing University, Chongqing 400044, China |
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| Abstract: | 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. |
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| Keywords: | weight total least square (WTLS) errors-in-observations (EIO) model parameter estimation cofactor matrix iterative algorithm |
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