SLRD-IMC: Structured Low-Rank Matrix Decomposition for Magnetic Anomaly Detection With Iteratively Merging Clusters (opens in new tab)

Magnetic anomaly detection (MAD) is pivotal for geophysical prospecting, particularly in defense and resource exploration. However, weak signals are often corrupted by electromagnetic interference and industrial noise, while conventional methods excessively focus on signal-to-noise ratio (SNR) improvement at the expense of structural fidelity. This study introduces a novel MAD framework integrating structured low-rank matrix decomposition with iteratively merging cluster (SLRD-IMCs). First, i...