面向浅海海底铁磁小目标的1D ViT-ResNet磁源定位方法OA

To address the challenges of magnetic signal acquisition in complex shallow-sea environments,this study designed and constructed a split towed system equipped with a fluxgate array.This system efficiently collected 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,based on the characteristics of measured data,a simulation dataset containing the passage characteristic curves of four types of target magnetic sources was constructed using COMSOL multiphysics simulation software,providing data support for model training.To meet the requirements of real-time detection and localization of magnetic sources,this study proposed a magnetic source localization method,named 1D ViT-ResNet,based on the collaboration of a one-dimensional vision transformer(1D-ViT)detection model and a one-dimensional residual network(1D-ResNet)localization model.Validation results using measured target signals show that the algorithm achieves a mean localization estimation error of approximately 7%.Compared with single-model approaches,the dual-model method reduces the false detection rate by an average of 11 percentage points,significantly improving the accuracy and reliability of underwater magnetic detection.