Research On Thinning Array Optimization Based On Modified Biogeography-based Optimization

Usually,large array antennas have a larger aperture and a higher-resolution in practical applications;however,its cost is higher.So thinned arrays are used to construction,keep its low costs,aperture unchanged and have superior side-lobe performance.The relative side-lobe level of the antenna array and the position of the element are 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.The aim of this paper: under the different array configuration,it is to find out how to arrange the array by selecting the appropriate array positions using the intelligent algorithm,which makes the relative side-lobe level of the array be reduced most greatly.As the intelligent algorithm has a slow convergence rate and easy to fall into the local optimal solution in the optimization process.In this paper,the target problem is solved by reducing the effect of the features to achieve the global relative side-lobe level and the position of the element optimal solution.The main work and innovation of this paper are as follows:1)The present situation of research on array thinned optimization using intelligent algorithms is summarized at home and abroad.2)The basic theory of array antenna and the mathematic model of thinning optimization array are presented as the theoretical basis of this paper.The influence of array formation on the relative side-lobe level and the optimal position of the array elements are discussed and analyzed.The relationship between some important performance indexes of the array antenna and the array parameters is analyzed and simulated.3)In this paper,firstly,a hybrid intelligent algorithm-Modified Biogeography Based optimization(MBBO)algorithm is proposed.In the Biogeography Based optimization algorithm,crossover and mutation operator of Genetic algorithm are introduced.Two operators are used to enhance the optimization speed and the population diversity of the algorithm.Then,MBBO is used to optimize thinned arrays.Compared with the Genetic algorithm,FFT algorithm and so on,MBBO has faster convergence speed,less chance of falling into the local optimal solution,better stability and wider application range than these.Secondly,a non-asymmetrical thinned arrays optimization model is proposed.In themodel,in order to reduce the required time in the optimization process,the array elements are uniformly arranged on both sides of the central axis of the arrays and the other elements are arranged at random in the remaining positions.Then,the intelligent algorithm is used to optimize and compare the three models of non-asymmetrical array,symmetric array and asymmetric array.4)From the thinning optimization of the linear array to the thinning optimization of the planar array,HG-BBO is used to optimize the array position of the planar array,so that the relative side-lobe level is well improved.