Phased Array Antenna Surface Deformation Reconstruction Based on Modal Low-Rank Correction and Gaussian Process Data Migration

Deformation of a phased array antenna surface can degrade its electrical performance. Conventional modal reconstruction depends on the accuracy of the structural model, while purely data-driven methods require extensive experimental data. We propose a reconstruction method that combines a modal prior, an input-dependent low-rank correction network, and Gaussian process data migration. Finite element modal analysis informs the baseline strain-to-displacement mapping. The correction network adapts this mapping to the input strain. Gaussian processes trained on experimental displacement residuals generate pseudo-experimental labels and confidence weights for fine-tuning. In the panel case study, the proposed method achieved a mean absolute error of 0.1596 mm and a maximum absolute error of 0.5963 mm. The corresponding errors for the conventional modal method were 1.5922 mm and 5.7291 mm. The proposed method retains an explicit strain-to-displacement mapping and uses a small experimental dataset.