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基于变分模态分解算法的多旋翼无人机航磁数据误差分析与处理研究

Research on aeromagnetic data error analysis and processing of multi-rotor UAV based on variational mode decomposition algorithm.

作者信息

Qiao Zhong-Kun, Yuan Peng, Hu Ruo, Wang Lin-Fei, Li Lin-Ling, Zhang Zong-Yu, Zhang Jia-Jun, Wu Bin, Lin Qiang

机构信息

Zhejiang Provincial Key Laboratory of Quantum Precision Measurement, College of Science, Zhejiang University of Technology, Hangzhou 310023, China.

Institute for Frontiers and Interdisciplinary Sciences, Zhejiang University of Technology, Hangzhou 310023, China.

出版信息

Heliyon. 2022 Nov 23;8(11):e11808. doi: 10.1016/j.heliyon.2022.e11808. eCollection 2022 Nov.

Abstract

Aeromagnetic survey of multi-rotor UAV is widely used in small and medium-sized mineral resources survey, engineering investigation, non-explosive detection and other fields due to its advantages of high safety, low cost and convenient operation. The original data of UAV aeromagnetic survey includes interference from external environment, interference from UAV platform and interference from airborne electromagnetic equipment. The interference is mainly shown as striping anomaly along the direction of the survey line in the aeromagnetic anomaly map, which affects the accuracy of aeromagnetic compensation and information detection of geological anomaly body, thus affecting the accuracy of interpretation of geological anomaly body. In this paper, the algorithm of Variational Modal Decomposition (VMD) is introduced to filter and preprocess the aeromagnetic data to obtain high quality aeromagnetic data. At the same time, the source and characteristics of the errors are predicted according to the interference size and spectrum characteristics of the Modal function errors, which provides a reference for the optimization of aeromagnetic system.

摘要

多旋翼无人机航磁测量因其安全性高、成本低、操作方便等优点,在中小型矿产资源勘查、工程勘察、非爆炸物探测等领域得到广泛应用。无人机航磁测量的原始数据包括来自外部环境的干扰、无人机平台的干扰和机载电磁设备的干扰。这种干扰主要表现为航磁异常图中沿测线方向的条带状异常,影响航磁补偿的精度和地质异常体信息的探测,进而影响地质异常体解释的准确性。本文引入变分模态分解(VMD)算法对航磁数据进行滤波和预处理,以获得高质量的航磁数据。同时,根据模态函数误差的干扰大小和频谱特征预测误差来源及特性,为航磁系统的优化提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d90/9706693/63acca089eae/gr1.jpg

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