Improve the performance of a linear array by changing the spaces among array elements in terms of genetic algorithm

Abstract

The pattern of linear array is optimized via adjusting the current allocations and positions of elements simultaneously in terms of improved genetic algorithm (GA). Optimized results show that minute modification of the element positions can improve the array pattern, especially for the fewer elements case. It is found that the improvements are attributed to additional side lobes, which involved some radiation energy and resulted in reduction of relative side lobe level (RSLL). In the optimal process, some skills, such as the soft constraints linked to the fitness function, the adaptive searching area, the injection of simulated annealing and immune operator etc., are used to make the algorithm more effective.