1D ViT-ResNet Method for Magnetic Source Localization of Small Ferromagnetic Targets on Shallow Seabeds

HUI Ran; LIANG Xiaofeng; GAO Haoran; YAN Shu

doi:10.11993/j.issn.2096-3920.2026-0057

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Article Navigation > Journal of Unmanned Undersea Systems > 2026 > Accepted Manuscript

HUI Ran, LIANG Xiaofeng, GAO Haoran, YAN Shu. 1D ViT-ResNet Method for Magnetic Source Localization of Small Ferromagnetic Targets on Shallow Seabeds[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2026-0057

Citation:

HUI Ran, LIANG Xiaofeng, GAO Haoran, YAN Shu. 1D ViT-ResNet Method for Magnetic Source Localization of Small Ferromagnetic Targets on Shallow Seabeds[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2026-0057

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1D ViT-ResNet Method for Magnetic Source Localization of Small Ferromagnetic Targets on Shallow Seabeds

doi: 10.11993/j.issn.2096-3920.2026-0057

MOE Key Laboratory of Marine Intelligent Equipment and System, Shanghai Jiao Tong University, Shanghai 201100, China

Received Date: 2026-03-25
Accepted Date: 2026-04-29
Rev Recd Date: 2026-04-27

Available Online: 2026-06-02

Abstract

Abstract

To address the challenges of magnetic signal acquisition in complex underwater environments, this study designed and constructed a modular towed-platform system equipped with a fluxgate magnetometer array. This system efficiently collects magnetic environmental noise and magnetic anomaly signals from four typical small ferromagnetic targets under dynamic conditions, successfully establishing a corresponding real-world measurement dataset . To compensate for the limitations of measured data and enhance data diversity, a simulation dataset was developed using COMSOL Multiphysics software, based on the characteristics of the real-world dataset. This dataset includes the magnetic source signature curves for the four target types, providing robust data support for model training. Ultimately, to enable real-time magnetic source detection and precise localization, this research proposes an innovative collaborative magnetic source localization method. This method integrates a 1D-ViT detection model with a 1D-ResNet localization model (hereinafter referred to as the 1D ViT-ResNet magnetic source localization method). Validated against real-world target signals, the algorithm achieved an average localization estimation error of approximately 7.0%. Compared to single-model approaches, this dual-model strategy significantly reduced the false detection rate, with an average reduction of 11.0 percentage points observed in real-world target signals, thereby substantially enhancing detection accuracy and system robustness .
- underwater magnetic detection,
- modular towed body system,
- fluxgate magnetometer array,
- 1D vision Transformer,
- residual network,
- magnetic anomaly localization

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References(16)

References

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