Research On Synthesis And Optimization Algorithm Of Sparse Antenna Arrays

Sparse arrays can not only reduce the number of array elements in order to cut down the engineering cost of the antenna system, but also has a greater degree of freedom to allocate array element over the aperture, achieving better performance of the antenna. Sparse arrays can obtain a narrow mainlobe and a lower peak sidelobe than uniform arrays with the same number of elements, aperture and minimum element spacing. At the same time, sparse arrays can weaken the mutual coupling between array elements due to relatively increased array element spacing. Therefore, sparse arrays has been widely used in practical engineering.The sidelobe level is increased with the decrease of the number of array elements for sparse arrays. In order to reduce the sidelobe level of the array, the element position and excitation are optimized. In this paper, the position of the element is optimized with the constraints of the array aperture, the number of elements and the minimum element spacing.This paper constructs the mathematical model of the sparse array according to the basic knowledge of the array antenna; thinned linear array and planar array are optimized by using Fourier algorithm; sparse linear arrays of four cases are optimized by using the modified genetic algorithm and the simulation results are compared with the optimized results of the literatures; the particle swarm optimization algorithm based on simulated annealing is also used to optimize the four kinds of linear sparse arrays and the simulation results are compared with that of the genetic algorithm and the literatures; finally, the particle swarm optimization algorithm based on simulated annealing is used to optimize the concentric ring sparse array. The simulation results show the high efficiency and convergence of the methods above.