Magnetic Anomaly Detection Method Based on Feature Fusion and Isolation Forest Algorithm

Magnetic Anomaly Detection Method Based on Feature Fusion and Isolation Forest Algorithm

In order to improve the weak magnetic detection ability under the background of Gaussian colored magnetic environment noise, a magnetic anomaly detection method based on feature fusion and isolation forest (IForest) algorithm is proposed in this paper. The method uses different feature algorithms to...

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Bibliographic Details
Main Authors: Ning Zhang, Yifei Liu, Lei Xu, Pengfei Lin, Heda Zhao, Ming Chang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Magnetic anomaly detection
feature fusion
unsupervised learning
isolation forest
principal component analysis
Online Access:https://ieeexplore.ieee.org/document/9852660/

Internet

https://ieeexplore.ieee.org/document/9852660/

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