Attention-Based ResNet for Radiation Pattern Prediction of Phased Array Antenna

In this letter, an attention-based residual network (ResNet) is proposed to predict the radiation pattern of phased array antenna (PAA). The proposed model consists of two input and preprocessing modules, a ResNet-attention module and a multilayer perception module. It enables simultaneous prediction of the radiation patterns for PAAs with multiple arrangements and frequencies, which supports the design of PAA and ensures the optimal performance of the equipment in the same electromagnetic environment. Various antenna arrays are utilized to verify the effectiveness and superiority of the proposed model. Discussions also encompass the model's performance under a large array and its generalization capabilities.