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Aeromagnetic Compensation Algorithm Based on Principal Component Analysis
Joint Authors
Fang, Guangyou
Zhu, Wanhua
Zhang, Qunying
Wu, Peilin
Chen, Luzhao
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-08
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Aeromagnetic exploration is an important exploration method in geophysics.
The data is typically measured by optically pumped magnetometer mounted on an aircraft.
But any aircraft produces significant levels of magnetic interference.
Therefore, aeromagnetic compensation is important in aeromagnetic exploration.
However, multicollinearity of the aeromagnetic compensation model degrades the performance of the compensation.
To address this issue, a novel aeromagnetic compensation method based on principal component analysis is proposed.
Using the algorithm, the correlation in the feature matrix is eliminated and the principal components are using to construct the hyperplane to compensate the platform-generated magnetic fields.
The algorithm was tested using a helicopter, and the obtained improvement ratio is 9.86.
The compensated quality is almost the same or slightly better than the ridge regression.
The validity of the proposed method was experimentally demonstrated.
American Psychological Association (APA)
Wu, Peilin& Zhang, Qunying& Chen, Luzhao& Zhu, Wanhua& Fang, Guangyou. 2018. Aeromagnetic Compensation Algorithm Based on Principal Component Analysis. Journal of Sensors،Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1201605
Modern Language Association (MLA)
Wu, Peilin…[et al.]. Aeromagnetic Compensation Algorithm Based on Principal Component Analysis. Journal of Sensors No. 2018 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-1201605
American Medical Association (AMA)
Wu, Peilin& Zhang, Qunying& Chen, Luzhao& Zhu, Wanhua& Fang, Guangyou. Aeromagnetic Compensation Algorithm Based on Principal Component Analysis. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1201605
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201605