Multi-strategy particle swarm optimization algorithm based on optical

This paper proposes a multi-strategy particle swarm optimization (MPSO) algorithm for optical phased array (OPA) phase noise compensation. The MPSO algorithm combines weight parameters and elite strategies to improve search efficiency and achieve global optimization. Simulation shows that the optimized optical phased array maintains a peak side-lobe ratio (PSLR) greater than 6.699 dB within a range of ±45 degrees. Compared with particle swarm optimization (PSO), genetic algorithm (GA) and stochastic parallel gradient descent (SPGD), the sidelobe suppression effect of the MPSO algorithm is improved by 4.00%, 50.30% and 1.35% respectively. Using a 32-element lithium niobate optical phased array at 1550 nm, the best performance occurs at a deflection angle of 0 degrees with a peak side-lobe ratio of 7.939 dB. The maximum beam scanning angle of 35° is achieved, and the peak side-lobe ratio is greater than 7 dB in the range of -17.5d° to 17.5°. These results demonstrate that the multi-strategy particle swarm optimization algorithm can effectively compensate for phase noise in optical phased arrays.