Abstract

在测量数据的获取过程中,常常存在着不确定性。它们影响着参数估计的有效性和可靠性。本文基于不确定性混合平差模型,在不确定性误差有界的约束下,利用随机误差和不确定性误差平方和达最小的新平差准则,给出了一个新的不确定性平差模型迭代算法。通过算例,对本文算法与其他方法进行了比较。结果表明:本文所提参数解算方法是有效可行的,且在不确定性较大时,该方法有较好的适用性。

Alternate abstract:

Uncertainty often exists in the process of measurement data acquiring,which affects the reliability and validity of parameter estimation.Based on uncertain mixed adjustment model,this paper applies the adjustment criterion,minimizing the sum of squares of random error and squares of uncertainty error,to study a new iteration algorithm to solve the adjustment model under the bound constrain of uncertainty.By the example,the estimation results of proposed method are compared with that of another relative method.The results show that the parameter calculation method presented in this paper is effective and feasible.Meanwhile,the method has satisfied applicability when the uncertainty is large.

Details

Title
系数矩阵中部分有界不确定性的混合平差算法
Author
王志忠; 宋迎春; 何玲莉
Pages
1171-1178
Publication year
2018
Publication date
Sep 2018
Publisher
Surveying and Mapping Press
ISSN
10011595
Source type
Scholarly Journal
Language of publication
English; Chinese
ProQuest document ID
2583562286
Copyright
© Sep 2018. This work is published under https://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.