摘要
综合了大地测量中各种异方差多源观测模型和联合平差方法,说明了混合估计方法可以用于测量数据融合,平衡附加信息和样本信息对参数估计的影响。通过求取权值使参数估计的协方差阵的迹最小的方法,给出了一个权的最优选择方法。本文扩展了已有的加权混合估计方法,使得新方法中的权不受验前单位权方差的限制,能有效应用于大地测量数据处理。
In this paper,multi-source observation models with various heteroscedastic and combined adjustment methods in geodesy are summarized.It shows that the mixed estimation method can be used for measurement data fusion,and can balance the influence of additional information and sample information on parameter estimation.By calculating the weights to minimize the trace of the covariance matrix of parameter estimation,an optimal selection method of weights is given.This paper extends the existing weighted mixing method so that the given method are not limited by the prior unit weight variance,and can be effectively applied to large measurement data processing.
作者
宋迎春
宋采薇
左廷英
SONG Yingchun;SONG Caiwei;ZUO Tingying(Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha 410083, China;School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)
出处
《测绘学报》
EI
CSCD
北大核心
2020年第1期34-41,共8页
Acta Geodaetica et Cartographica Sinica
基金
国家自然科学基金(41574006
41674009
41674012)~~
关键词
随机约束
平差模型
加权混合估计
最优线性无偏估计
stochastic constraint
adjustment model
weighted mixed estimation
optimal linear unbiased estimation
