• Guanyi Zhao, Qi Han, Xiang Peng, Pengyi Zou, Haidong Wang, Changping Du, He Wang, Xiaojun Tong, Qiong Li, and Hong Guo.
• School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
• Sensors (Basel). 2019 Jul 3; 19 (13).

AbstractAeromagnetic 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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