Optimizing the Architecture of Planar Phased Array by Improved Genetic Algorithm

An architecture optimizing method in planar phased array is given based on genetic algorithm (GA). Pattern sidelobe is improved by optimizing array architecture via division of subarrays. Analyze subarray pattern and give out the flow chart of subarray segmentation. By adaptive crossover operator and independent genetic operation, traditional GA is improved. Convergence speed is accelerated and calculation efficiency is enhanced remarkably. Simulations of segmenting 24times28 array into 50 subarrays are provided. Pattern sidelobe is improved by 14.22 dB after 60 generations of GA.