A Weighted Mixed Estimation Method with Bounded Uncertainty

被引：0
|
作者：
Song Y. [1 ,2 ,3 ]
Song C. [1 ,2 ,3 ]
Zuo T. [1 ,2 ,3 ]
机构：
[1] Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha
[2] Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Changsha
[3] School of Geosciences and Info Physics, Central South University, Changsha
来源：
Zuo, Tingying (dengmin208@tom.com) | 1600年 / Wuhan University卷 / 45期
基金：
中国国家自然科学基金;
关键词：
Bounded uncertainty; Information fusion; Set membership estimation; Sochastic constraint; Weighted mixed estimation;
D O I：
10.13203/j.whugis20180300
中图分类号：
学科分类号：
摘要：
The mixed estimation is necessary for fusion of various heteroscedastic multi-source observation models in geodesy. Because the additional constraints and the sample information play an unequal role in the estimation process, we need to establish a new weighted adjustment criterion to balance the influence of prior constraints and observation information on parameter estimation. Firstly we regard multi-source observation data as observation information and some random constraints information, use ellipsoid approximation to describe bounded uncertain information, and establish an adjustment criterion based on the minimum trace of outer ellipsoid characteristic matrix. Then, we propose a new method of observational information fusion and a method of calculating optimal weights, which makes the weighted mixed estimation method effective in geodetic data processing. Finally, the validity of the algorithm is verified by an example, and the relationship between the set membership estimation solution and the weighted mixed estimation is illustrated. © 2020, Editorial Board of Geomatics and Information Science of Wuhan University. All right reserved.
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页码：949 / 955
页数：6
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