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Q1 2026

Single vector magnetometer moving direction magnetic gradient anomaly detection method

Qian Xiang · Pei Jiang · Ning Zhang
10.1186/s44147-026-01094-4 380 Views 0 Citations
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Abstract

Abstract
In this paper, aiming at the problems of complex array calibration and insufficient detection performance under low signal—to—noise ratios in existing vector gradient magnetic anomaly detection systems, a magnetic anomaly detection method based on constructing an Orthogonal Basis Function (OBF) detector using the magnetic gradient in the moving direction of a single vector magnetometer is proposed. Firstly, multiple error sources in the magnetic field measurement of the vector magnetometer are analyzed, and a comprehensive error model is established. On this basis, an OBF detector for magnetic gradient anomalies in the moving direction of a single vector magnetometer is developed, and the influences of factors such as the geomagnetic background field, platform oscillation, and spatial sampling interval on its performance are analyzed. Simulation experiments show that the method proposed in this paper outperforms the traditional dual—sensor vertical array magnetic gradient anomaly OBF detection method under conditions of low noise ratios and platform oscillation. Field experiments based on MEMS vector magnetometers further verify its effectiveness in magnetic anomaly detection. This method has the advantages of strong real—time performance, low cost, and small size, and shows great application prospects in scenarios such as dangerous object detection and explosion disposal, and intrusion monitoring.

Cite this Article (APA)
Qian, X., Pei, J., Ning, Z. (2026). Single vector magnetometer moving direction magnetic gradient anomaly detection method. Journal of Engineering and Applied Science. https://doi.org/10.1186/s44147-026-01094-4
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Published in
ISSN 1110-1903
Quartile Q1
AMS Score 100
Field Engineering & Technology
Publisher Cairo University, Faculty of Engine
Country 🇪🇬 Egypt
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Publication Details
Year 2026
Language English
Added 24 Aug 2026