Comparison between optimal configuration algorithms of fiber phased array

Abstract

Optical fiber phased array can be used in high-power laser beam combination, lidar and other areas. The configuration of the optical fiber array is different from the microwave phased array, which has periodic problems that affect the energy intensity distribution of the main lobe. Starting from the physical model, in this paper we establish a theoretical model of optical phased array antenna array based on a set of concentric circular ring lattices, and propose a theory of the rapid synthesis of randomly configured interference field strengths through using analytical continuation method and Fourier transform method. The problem of sampling bandwidth and sampling number that should be paid attention to in the numerical simulation of discrete sampling are discussed, and the problem of quickly realizing the numerical simulation of multi-beam interference field is solved. Genetic algorithm and particle swarm algorithm for optimizing the configuration of optical phased array antennas are investigated with different populations. The convergence speeds and optimization efficiencies of the two algorithms are compared and analyzed. It is demonstrated that the peak side-lobe ratio PSR can be achieved to be better than 0.270 by the genetic algorithm optimized configuration array under the real fabricate parameter. The proposed method is expected to be used in the actual optical phased array antenna configuration to guide the optimal design of the antenna with low side lobes, and the proposed model is also expected to provide a certain reference value for the study of optimizing the non-differentiable objective function.