| Array antennas have a wide range of applications in mobile communication,radar,satellite communication and other fields,where beam assignment is one of the key technologies of array antennas,and it is of great importance to study beam assignment technology.In recent years,it has become a hot spot and focus of research to get the required directional map of the array antenna quickly by intelligent optimization algorithm to achieve the effect of beam assignment.In this paper,we use the improved particle swarm algorithm to realize the beam assignment of array antennas.To address the problem of weak search capability of particle swarm algorithm in the later stage,two different improved particle swarm algorithms are composed by introducing adaptive inertia weights and combining particle swarm algorithm with butterfly algorithm to accelerate the convergence speed of the algorithm and improve the global search capability.These algorithms are then applied to a specific beam assignment problem.The main work and innovations of this paper are as follows.1.Introducing the basic theory of array antenna,including uniform linear array directional map function,planar array directional map function and so on.The research significance of beam assignment is analyzed,and the application of intelligent algorithms in beam assignment of array antennas is studied.2.To address the problems of slow convergence and easy to fall into local optimum of the standard particle swarm algorithm in beam assignment problem,the adaptive inertia weight particle swarm algorithm is improved.The adaptive inertia weights can balance the global search ability and local search ability of the algorithm according to the change of the current fitness value and the change of the iteration progress,so that the historical optimal solution can continue to be updated in the late iteration to get rid of the "premature" convergence.3.Combining the particle swarm algorithm with the particle update mechanism of the butterfly algorithm,the butterfly-particle swarm algorithm is proposed.When the standard particle swarm algorithm no longer continues to converge,the algorithm uses the particle update mechanism in the butterfly algorithm and adds the Levy flight factor to generate random perturbations to obtain new particles with higher scores,and then uses the "elite" particle screening mode to eliminate the lower scoring particles,making the algorithm have better convergence capability.4.The adaptive inertia weight method,butterfly-particle swarm algorithm and another improved particle swarm algorithm,the adaptability correlation method,are used to optimize the feed amplitude and phase of the linear array antenna,to achieve the residual cut square directional map,wide zero limit directional map and different left and right subflap directional maps.The simulation results are compared and analyzed with the standard particle swarm optimization results to verify the effectiveness of the three algorithms in the beam assignment problem.5.The optimization of the planar array antenna is carried out by using three algorithms.By optimizing the position of the array element of the planar array,the grid flap suppression and maximum sub-flap reduction are achieved;based on the optimization using only the position,a new idea of increasing the feed amplitude of the antenna unit as the optimization object is proposed,which can further reduce the sub-flap level under the same conditions,and it is proved that in the problem of sub-flap reduction of large pitch antenna array,increasing the optimization object can get better optimization results. |
