空军工程大学学报2026，Vol.27Issue(2)：42-53,12.DOI:10.3969/j.issn.2097-1915.2026.02.006
基于U-Net神经网络构建三维磁基准图方法研究
Research on Construction Method of 3D Geomagnetic Reference Map Based on U-Net Neural Network
摘要
Abstract
The downward continuation algorithm of geomagnetic potential field is a typical ill-posed prob-lem in mathematics.Aimed at the problems that the traditional downward continuation of geomagnetic da-ta is susceptible to the effects of noise and continuation distance,this paper explores the downward contin-uation of magnetic anomalies by using the U-Net neural network.Magnetic anomalies obtained at different heightsvia forward modeling of simple prisms and complex combined prisms,are taken to be labels of ma-chine learning with 5 000 label groups being constructed for each dataset.The dataset is divided into train-ing,test,and validation sets at a ratio of 8∶1∶1.The construction of machine learning labels is in com-prehensive consideration information such as geometric position of the model center,the length,width,and height of the model,as well as magnetic inclination,magnetic declination,and magnetization intensi-ty.Under condition of interference-free experiments,the average relative prediction accuracy is 97.0％for the single prism model and 95.2％for the three-combined prism model.Under the interference of 5％Gaussian noise,the average relative prediction accuracy of the combined model remains 94.9％,showing excellent anti-interference performance.And simultaneously,the model exhibits strong distance robust-ness within the range of continuation distances involved in the experiments.This study verifies that the U-Net network can effectively realize downward continuation and has broad application prospects in the con-struction of 3D magnetic reference maps.关键词
磁基准图/机器学习/向下延拓/磁导航/磁数据Key words
geomagnetic reference map/machine learning/downward continuation/geomagnetic naviga-tion/geomagnetic data分类
航空航天引用本文复制引用
郝奥伟,胡景,纪晓琳,杨宾锋,郭娇娇,刘嘉正,冶得成..基于U-Net神经网络构建三维磁基准图方法研究[J].空军工程大学学报,2026,27(2):42-53,12.基金项目
国家自然科学基金(42404082,42104051) （42404082,42104051）
陕西省自然科学基础研究计划(2024JC-YBQN-0260) （2024JC-YBQN-0260）
