【摘要】 天线阵列的相对旁瓣电平和阵元位置为非线性关系。对于非线性关系求最优值问题,用其他优化算法较难求解,而研究采用智能算法求解是一条值得探索的可行路径。提出了一种混合智能算法——改进生物地理学算法,即对生物地理学算法的迁移算子和变异算子进行改进,以提高种群的进化速率,进而优化对称和非对称稀疏平面阵列。仿真结果表明,与以往的算法相比,该算法提高了优化速率,降低阵列的相对旁瓣电平;阵元在阵列孔径内非对称分布比对称分布,所获得的旁瓣电平更低。更多还原

【Abstract】 The relation between the relative side-lobe level of the antenna array and the position of the element is non-linear.It is usually difficult to solve the optimal value problem of nonlinear relation with other optimization algorithms,and it is a feasible way to explore the solution using the intelligent algorithm. In order to improve the rate of population evolution and optimize symmetric and asymmetric thinned planar arrays,a hybrid intelligent algorithm,or Modified Biogeography Based Optimization( MBBO) algorithm is proposed,and the migration and mutation operators are improved in the algorithm. Simulation results show that compared with the previous algorithms,the proposed algorithm improves the optimization rate and reduces the relative side-lobe level of the array. The obtained side-lobe level is lower in the case of asymmetric distribution of the element in the aperture of the array than in the case of symmetry distribution.更多还原