Large Thinned Array Design Based on Multi-objective Cross Entropy Algorithm - 边莉 边晨源 王书民 (Shanghai jiao tong da xue xue bao, 2015)
To consider multi-objective optimization problem with the number of feed array elements and sidelobe level of large antenna array, multi-objective cross entropy（CE） algorithm is proposed by combining fuzzy c-mean clustering algorithm with traditional cross entropy algorithm, and specific program flow of the algorithm is given.Using the algorithm, large thinned array（200 elements） given sidelobe level（-10,-19 and-30 d B） problem is solved successfully. Compared with the traditional statistical algorithms, the optimization results of the algorithm validate that the number of feed array elements reduces by 51%, 11% and 6% respectively. In addition, compared with the particle swarm optimization（PSO） algorithm, the number of feed array elements from the algorithm is more similar, but the algorithm is more efficient.