Ultra-Wide-Scanning Conformal Heterogeneous Phased Array Antenna Based on Deep Deterministic Policy Gradient Algorithm
Binchao Zhang, Cheng Jin, Kaiqi Cao, Qihao Lv, Pengyu Zhang, Yan Li, Maokun Li
Abstract
This article investigates the pattern synthesis of the conformal phased array antenna (PAA) by using the deep deterministic policy gradient (DDPG) algorithm, and a nearly full solid angle for beam steering is realized. The beam steering capability of the planar and conformal PAAs is theoretically compared at first, and a conclusion is obtained that conformed to the conical-and-cylindrical structure can help to achieve ultrawide-angle beam steering. Next, a typical deep reinforcement learning algorithm, which is the DDPG algorithm, is utilized to deal with the fast beam steering problem of the conformal heterogeneous PAA. By virtue of the strong fitting ability of the DDPG algorithm for high-dimensional continuous nonlinear problems, the performance of fast beam steering is achieved within a wide-angle range within (−150°, 150°). Finally, a prototype of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1\times17$ </tex-math></inline-formula> conformal PAA is fabricated for measurement and verification, and the measured results are in good agreement with the simulation results.