An Aeromagnetic Compensation Method Based on a Multimodel for Mitigating Multicollinearity
An Aeromagnetic Compensation Method Based on a Multimodel for Mitigating Multicollinearity
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一种基于多模型的减轻多重共线性的航磁补偿方法
DOI：
10.3390/s19132931
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发表时间：
2019-07
期刊：
影响因子：
--
通讯作者：
Guo Hong
中科院分区：
文献类型：
--
作者：
Zhao Guanyi;Han Qi;Peng Xiang;Zou Pengyi;Wang Haidong;Du Changping;Wang He;Tong Xiaojun;Li Qiong;Guo Hong
航空磁测在地球物理勘探和其他许多领域中发挥着重要作用。在许多应用中，磁力计安装在飞机上以测量大面积。由于其组成，飞机有自己的磁场，这降低了测量的可靠性，因此需要一种减少磁干扰场效应的技术（称为航空磁补偿）。通常，基于Tolles-Lawson模型，这个问题被解决为线性回归问题。然而，多重共线性，这是指当两个以上的模型变量是高度线性相关的情况下，在估计模型系数时产生的准确性问题。分析结果表明，引起复共线性的变量与飞行航向有关。针对这一点，提出了一种多模型补偿方法。通过选取对多重共线性贡献较小的变量，建立不同的子模型来描述飞机在不同方向飞行时的磁干扰。该方法抑制了复共线性的影响，提高了测量的可靠性。与现有方法相比，该方法能更有效地减小干扰场，并通过一组机载试验进行了验证。
Aeromagnetic surveys play an important role in geophysical exploration and many other fields. In many applications, magnetometers are installed aboard an aircraft to survey large areas. Due to its composition, an aircraft has its own magnetic field, which degrades the reliability of the measurements, and thus a technique (named aeromagnetic compensation) that reduces the magnetic interference field effect is required. Commonly, based on the Tolles–Lawson model, this issue is solved as a linear regression problem. However, multicollinearity, which refers to the case when more than two model variables are highly linearly related, creates accuracy problems when estimating the model coefficients. The analysis in this study indicates that the variables that cause multicollinearity are related to the flight heading. To take this point into account, a multimodel compensation method is proposed. By selecting the variables that contribute less to the multicollinearity, different sub-models are built to describe the magnetic interference of the aircraft when flying in different orientations. This method restricts the impact of multicollinearity and improves the reliability of the measurements. Compared with the existing methods, the proposed method reduces the interference field more effectively, which is verified by a set of airborne tests.
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影响因子：
0.9
作者：
C. Hardwick
通讯作者：
C. Hardwick
影响因子：
--
作者：
G. Noriega;Andre Marszalkowski
通讯作者：
G. Noriega;Andre Marszalkowski
影响因子：
1.6
作者：
MCGREGOR, DD
通讯作者：
MCGREGOR, DD
影响因子：
1.4
作者：
B. Leach
通讯作者：
B. Leach
DOI：
10.1071/aseg2016ab300
发表时间：
2016-12
期刊：
ASEG Extended Abstracts
影响因子：
--
作者：
Dailei Zhang;Danian Huang;Junwei Lu;Boyuan Zhu
通讯作者：
Dailei Zhang;Danian Huang;Junwei Lu;Boyuan Zhu