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Related Experiment Video

Updated: Jun 11, 2025

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement

Published on: November 7, 2017

A Remote Two-Point Magnetic Localization Method Based on SQUID Magnetometers and Magnetic Gradient Tensor Invariants.

Yingzi Zhang¹, Gaigai Liu¹, Chen Wang¹

¹State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.

Sensors (Basel, Switzerland)

|September 28, 2024

Summary

This summary is machine-generated.

A new magnetic localization method using SQUID sensors extends detection range to 500m. This advanced technique accurately pinpoints targets with minimal error, overcoming limitations of existing magnetic gradient tensor (MGT) methods.

Keywords:

magnetic anomaly detection magnetic gradient tensor magnetic localization superconducting quantum interference device

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Last Updated: Jun 11, 2025

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Area of Science:

Physics
Geophysics
Sensor Technology

Background:

Existing two-point magnetic gradient tensor (MGT) localization methods are limited to a 2.5m detection distance.
These methods require prior knowledge of the target's magnetic moment vector, which is often unknown.
Real-time, remote localization remains a challenge for current MGT techniques.

Purpose of the Study:

To develop a novel two-point magnetic localization method for remote and real-time target detection.
To overcome the distance and unknown magnetic moment limitations of existing MGT localization systems.
To enhance interference suppression capabilities for improved localization accuracy.

Main Methods:

Utilized self-developed, ultra-sensitive superconducting quantum interference device (SQUID) magnetometers.
Employed magnetic gradient tensor (MGT) invariants within a linear positioning model.
Incorporated a quasi-Newton optimization algorithm for advanced interference suppression.

Main Results:

Simulations indicate a potential detection distance of 500m using the superconducting MGT system.
The proposed method achieved significantly less than 1% relative localization error in non-blind areas, outperforming NSPT and XTPT methods.
Experimental validation at 10m distance yielded a minimum relative localization error of 4.5229%.

Conclusions:

The proposed SQUID-based MGT localization method offers a significant advancement in remote sensing capabilities.
The method effectively calculates both magnetic moment and relative position vectors, enhancing localization accuracy.
It provides a robust solution for real-time, long-distance magnetic target localization with improved error performance.