An Efficient Array Synthesis Method for Reconfigurable Reflectarray Antennas Based on a Macroscopic Model of Metasurface

A more efficient and accurate array synthesis method for reconfigurable reflectarray antenna (RRA) is proposed. A macroscopic model of digital coding metasurface that can take the mutual coupling of adjacent elements into account is utilized to replace array theory in traditional synthesis method, making the numerically calculated far-field patterns closer to full-wave simulated ones. Then, the macroscopic model is integrated with genetic algorithm (GA) to realize an efficient and accurate array synthesis method. A <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$32\times 32$</tex>-element RRA is designed to verify the macroscopic-model-genetic-algorithm (MM-GA) array synthesis method. Compared with the array-theory-genetic-algorithm (AT-GA) method, our proposed MM-GA performs better in full-wave simulations. The full-wave simulated sidelobe level by MM-GA synthesis is 15.3dB, while that of AT-GA is 14.8dB, when the RRA scans to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\varphi=90^{\circ}, \theta=45^{\circ}$</tex>.