Research On 3D Array Antenna Optimization Method Based On Improved Moth Suppression Algorithm

As the major fields of communication gradually unveil the 5G mystery,the core antenna array has gradually become the object of people's research.In view of the limited energy,this study intends to improve the coverage of the array antenna signal energy under the existing conditions.Because the traditional two-dimensional array antenna has the disadvantage of low accuracy in estimating the elevation angle,this paper proposes a study on the suppression of sidelobe levels of the three-dimensional array antenna based on an improved moth flutter algorithm as follows:(1)An array antenna model is proposed.Based on the two-dimensional array pattern function,a three-dimensional array antenna array factor expression is derived through the transformation of a rectangular coordinate system.In an omnidirectional point source radiation source,according to the array factor A mathematical model of the sidelobe level of the three-dimensional array antenna was constructed with the expression ratio of the maximum array factor,and the maximum sidelobe level decibel was used as the objective function.Two comparison algorithms of harmony search and cuckoo are proposed,and the three-dimensional array antenna sidelobe suppression combined with array element size(16 and 32)and array optimization parameters(optimizing excitation current and simultaneously optimizing excitation current and array geometric position)is used as Application comparison.(2)In view of the fact that the native moth fire suppression algorithm is prone to fall into the local optimum,unable to jump out and premature convergence,this paper proposes two improved moth fire suppression algorithms(ALO_MFO and ACO_MFO).The ALO_MFO algorithm references the MFO spiral The flight formula,combined with the ant's adaptive random walk and elite strategy in the ant lion algorithm(ALO),first introduces the ant's adaptive random walk,and moves the range of all ants(solutions)along with the ant around the ant lion trap.The increase in the number of walks reduces,and the range of the solution is stabilized by the elimination mechanism within the population,thereby increasing the stability of the algorithm.The elite strategy is to influence the global solution through the elite ant lion,so that the individual population moves with the global optimal solution(elite individual)and the historical optimal solution direction.This paper proposes three algorithms for comparison,and proves that the algorithm has good optimization performance through experiments.(3)Propose another ACO_MFO algorithm.This algorithm first introduces the Monte Carlo method for initialization based on moth fluttering.In order to avoid falling into local optimum,the pheromone is combined with the ant colony algorithm to find the best.The path optimizes the inferior solution,does not adjust the superior solution,and makes small ants of the intermediate solution(the range of its movement gradually decreases as the number of iterations increases),thereby adjusting the global optimization of the individual who is trapped in the local optimum.The guidance ability improves the convergence accuracy of the algorithm.Finally,the improved algorithm is applied to the suppression of the sidelobe of the three-dimensional array antenna pattern,and an antenna pattern with stronger mainlobe directivity and a lower maximum sidelobe level is obtained.,Can finally get the best solution according to specific conditions.(4)Using the geometric position and excitation current of the array element in the optimization model,the simulation experiments of the sidelobe suppression of the three-dimensional array antenna in two scenarios of the array element size of 16 and 32 are obtained,which has stronger main lobe directivity and lower The side lobe level pattern is then compared with the harmony search optimization algorithm(HS),cuckoo algorithm(CS),and moth flare algorithm(MFO)in simulation experiments,which proves that the two improved algorithms in this paper are in the signal beam Radiation optimization shows better performance.