Flow-Based Electromagnetic Information Recovery for Inaccessible Area and Low-Resolution Detection

Metasurfaces are widely applied in various applications, such as none-line-of-sight detection, radar imaging enhancement, and non-invasive monitoring. However, electromagnetic (EM) information recovery in inaccessible and occluded areas is of great importance to obtain complete EM picture, albeit challenging. Conventional methods to this end typically necessitate specific prior knowledge and suffer from performance degradation due to implicit computation mechanism. Here a flow-based framework is proposed to facilitate the explicit computation of conditional distribution between the partially accessible EM field and complete EM field. The adjacent distributions in a hierarchical architecture exhibit similarity and seamless convertibility between each other, facilitating a smooth transition without performance degradation. The method is benchmarked through two typical scenarios, i.e., resolution enhancement and field recovery in randomly occluded areas. Even in an entirely unseen scene, the EM information recovery maintains consistence with the ground truth, with maximum error below 10%. The work provides a key advance for EM information recovery in complex real-world environment, offering fresh insights on information access and detection even in extreme cases.