ROM-Based Real-Time Analysis of Electromagnetic Performance for APAA in a Digital Twin System

During the service process of active phased array antenna (APAA), factors such as array heating and wind loading cause significant deformation, which will seriously affect the electromagnetic (EM) performance. Obtaining the geometric parameters of the array through sensors and predicting the real-time EM performance based on the digital twin (DT) technique are crucial to guarantee the service quality of the array antenna (e.g., the detection accuracy of a target). Traditional offline simulation methods can calculate the real EM performance of APAA with geometric errors. However, it requires a large number of computational resources and computation time, which is difficult to meet the demand for real-time prediction in DT. In this article, a generalized DT framework based on the reduced-order model for APAA is proposed. First, we introduce a dynamic-static attention-enhanced convolutional network for real-time computation of key EM indicators. Then, a super-resolution generating network is proposed, which realizes the mapping of array geometrical errors to the 3-D far-field pattern, and provides support for comprehensive performance evaluation. The framework proposed in this article constructs a twin model of APAA, realizes the virtual-reality mirroring of the EM performance, and is deployed and applied in an APAA DT platform.