宋迎春, 宋采薇, 左廷英. 带有界不确定性的加权混合估计方法[J]. 武汉大学学报 ( 信息科学版), 2020, 45(7): 949-955. DOI: 10.13203/j.whugis20180300
引用本文: 宋迎春, 宋采薇, 左廷英. 带有界不确定性的加权混合估计方法[J]. 武汉大学学报 ( 信息科学版), 2020, 45(7): 949-955. DOI: 10.13203/j.whugis20180300
SONG Yingchun, SONG Caiwei, ZUO Tingying. A Weighted Mixed Estimation Method with Bounded Uncertainty[J]. Geomatics and Information Science of Wuhan University, 2020, 45(7): 949-955. DOI: 10.13203/j.whugis20180300
Citation: SONG Yingchun, SONG Caiwei, ZUO Tingying. A Weighted Mixed Estimation Method with Bounded Uncertainty[J]. Geomatics and Information Science of Wuhan University, 2020, 45(7): 949-955. DOI: 10.13203/j.whugis20180300

带有界不确定性的加权混合估计方法

A Weighted Mixed Estimation Method with Bounded Uncertainty

  • 摘要: 大地测量中各种异方差多源观测模型进行融合都需要进行混合估计。由于附加信息和样本信息在估计过程中作用是不均等的,需要建立新的加权平差准则,平衡先验约束和观测信息对参数估计的影响。把多源观测数据看成是观测信息和一些随机约束信息,首先利用椭球近似描述有界不确定信息,建立了基于外接椭球特征矩阵迹最小的平差准则,然后提出了一个新的观测信息融合方法,并给出了一种优化权的计算方法,使得加权混合估计方法能有效应用于大地测量数据处理,最后,通过算例验证了算法的有效性,说明了集员估计解与带权混合估计的关系。

     

    Abstract: 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 approxima-tion 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.

     

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