Ocean Ultra/Extremely Low-Frequency Magnetic Field Detection System Based on Highly Sensitive Magnetoelectric Sensors

Magnetoelectric magnetic sensors (MESs) magnetic sensors (MSs) have attracted much attention because of their high sensitivity, low noise, and power consumption. They have been gradually studied in the field of magnetic field detection of marine targets. In this article, we proposed a novel ocean bottom magnetic (OBM) receiver based on our highly sensitive ME MES. The sensitivity of such sensors is higher than 18 V/Oe from 0.2 to 10.0 Hz, which is better than the current international leading Mag-13 fluxgate sensor. Its equivalent magnetic noise is close to 7 pT/<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\surd $ </tex-math></inline-formula>Hz at 1 Hz. Using two single-axis MESs to form a set of horizontal orthogonal measured modes, the OBM receiver can detect the ship’s ultra/extremely low-frequency (ULF/ELF) vector magnetic signals. Furthermore, the performance of such a system has been demonstrated by performing a marine experiment using an artificial source (electric dipole source) that can generate standard ULF/ELF signals. The results show that the measured data of the OBM receiver are in good agreement with the simulated data, and the maximum error at the extreme value is less than 20%. This work will provide critical technical support for MESs in marine target detection and has excellent potential application prospects.

Authors

Institutions

Publication Details

Journal
IEEE Sensors Journal
Published
2024-12-19
DOI
https://doi.org/10.1109/jsen.2024.3516739
Citations
3
Primary Topic
Geoscience and Mining Technology
Type
article
Field-Weighted Citation Impact
1.09

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ocean Ultra/Extremely Low-Frequency Magnetic Field Detection System Based on Highly Sensitive Magnetoelectric Sensors

Lindong Pan, Junqi Gao, Qingwei Liu, Ying Shen et al.
3 citations
IEEE Sensors Journal
Geoscience and Mining Technology
1.09
article

Ocean Ultra/Extremely Low-Frequency Magnetic Field Detection System Based on Highly Sensitive Magnetoelectric Sensors

Lindong Pan, Junqi Gao, Qingwei Liu, Ying Shen, Bing Li, Hongliang Zhang
article en
3 citations

Abstract

Magnetoelectric magnetic sensors (MESs) magnetic sensors (MSs) have attracted much attention because of their high sensitivity, low noise, and power consumption. They have been gradually studied in the field of magnetic field detection of marine targets. In this article, we proposed a novel ocean bottom magnetic (OBM) receiver based on our highly sensitive ME MES. The sensitivity of such sensors is higher than 18 V/Oe from 0.2 to 10.0 Hz, which is better than the current international leading Mag-13 fluxgate sensor. Its equivalent magnetic noise is close to 7 pT/<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\surd $ </tex-math></inline-formula>Hz at 1 Hz. Using two single-axis MESs to form a set of horizontal orthogonal measured modes, the OBM receiver can detect the ship’s ultra/extremely low-frequency (ULF/ELF) vector magnetic signals. Furthermore, the performance of such a system has been demonstrated by performing a marine experiment using an artificial source (electric dipole source) that can generate standard ULF/ELF signals. The results show that the measured data of the OBM receiver are in good agreement with the simulated data, and the maximum error at the extreme value is less than 20%. This work will provide critical technical support for MESs in marine target detection and has excellent potential application prospects.

IEEE Sensors JournalVol. 25(3)
Harbin Engineering University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Heilongjiang Province
Life below water
Openalex Percentile: Top 22%
Geoscience and Mining Technology
1.09
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.