Efficient Inversion of Multiple Magnetic Dipole Models Based on Deep Learning Prior Analysis and Penalty Function Optimization (opens in new tab)

The inversion of multiple magnetic dipoles plays a critical role in applications such as geological exploration and spacecraft magnetic modeling. The primary challenges include an unknown number of magnetic sources, high sensitivity to noise, and low inversion accuracy. In this article, we propose a novel 3-D inversion method for multiple magnetic dipole models that integrates deep-learning-based prior analysis with a penalty function optimization strategy. A lightweight convolutional attenti...