An Aeromagnetic Compensation Method Based on a Multimodel for Mitigating Multicollinearity

Abstract

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.

Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets

“…This weighted-fusion data set was analyzed in the follow-up works. Moreover, the multicollinearity among separate sensors hindered the establishment of regression models, and the feature data with high correction might lead to incorrect discrimination and prediction [40]. In the study, Pearson coefficient analysis and variance inflation factor (VIF) analysis were used for optimizing the fusion matrixes by decreasing the multicollinear information, and the total four new fusion data sets (direct-fusion data set, weighted-fusion data set, optimized direct-fusion data set, and optimized weighted-fusion data set) were analyzed in follow-up studies.…”

Unmanned Aerial Vehicles for Magnetic Surveys: A Review on Platform Selection and Interference Suppression

“…Although nonmagnetic materials are used as much as possible in the design, some modules and structures of the UAVs still contain ferromagnetic materials (e.g., engines, motors), magnetic fields generated by these ferromagnetic materials and the electromagnetic fields generated by the airborne electronic system during operation contribute to the main components of the interference. In fact, this problem also exists in traditional aeromagnetic surveys [45][46][47]. The suppression of the interference field generated by the platform is also called compensation.…”

Analyze and improve the influence of geomagnetic gradient on aeromagnetic compensation in a towed bird

“…In 1980, Leach used linear regression theory to study the T-L model and proposed a ridge regression algorithm to solve the multicollinearity problem in the aeromagnetic compensation model (Leach, 1980). In recent years, the main methods to solve multicollinearity problems are the principal component analysis (Wu et al, 2018), the truncated singular value decomposition (TSVD) (Gu et al, 2013;Deng et al, 2013), the multi-model compensation method (Zhao et al, 2019), the wavelet analysis method (Deng et al, 2010;, and the improved recursive least-squares (Zhao et al, 2017). The above methods are all based on linear models.…”