A Dual DNNs Method for Real-Time Beam Scanning and Stabilization of Deformed Conformal Array Antenna

This letter presents a method utilizing dual deep neural networks (DNNs) for real-time beam stabilization and scanning capability restoration in deformed conformal array antenna. Initially, the physical-driven DNNs based on active element pattern are trained to swiftly generate the phase for directional control. Based on the prerained neural networks, the physical-driven DNNs semidefinite relaxation algorithm is proposed to generate the amplitude that meets the requirements of the desirable radiation pattern. The data-driven DNNs are subsequently employed to achieve real-time amplitude output based on the existing amplitude as training data. Simulation and measured results demonstrate that the proposed methods can rapidly output the amplitude and phase corresponding to the desired radiation pattern. It combines the advantages of DNNs and convex optimization algorithm and achieves a good tradeoff between both methods.