Research On Sparse Optimization Method Of Array Antenna

Antenna is an important part of wireless communication terminal in the technologically advanced society and its research has attracted tremendous attention from many scholars.However,with the development of science and technology,a single antenna cannot meet the need of practical engineering.As a result,array antenna is begin to be applied in many projects.Although the radiation characteristic of is better than that of single antenna,the array antenna still contains many disadvantages,including large number of elements,large size and high cost.Therefore,how to reduce the number of array elements and save the engineering cost without affecting the radiation characteristics of array antenna are challenges for the design of array antenna.The sparse distribution optimization of array antenna is a research hotspot in recent years.This technique can reduce the number of elements and rearrange the array elements.There are many methods of sparse array optimization,such as traditional iterative algorithm based on population,matrix bundle algorithm and related improved algorithm.These sparse optimization methods can reduce the number of elements as well as the cost of array design.The main contents and innovations of this paper are as follows:Firstly,the basic principles of genetic algorithm and particle swarm optimization are introduced,and the optimization process of these two traditional algorithms are described and the sparse distribution optimization of uniform linear array is carried out.In view of the shortcomings of the traditional algorithm,a non-linear dimension reduction idea is introduced into the algorithm while the principle and process of dimension reduction are described,and the feasibility of dimension reduction idea is verified by test function.Besides,the traditional algorithm combined with the idea of dimension reduction is used to optimize the sparse distribution of uniform linear array,and the performance of the algorithm before and after the introduction of dimension reduction strategy is compared.Secondly,the basic principle of matrix beam algorithm and its improved algorithm is introduced.The traditional algorithm and matrix beam algorithm combined with dimension reduction idea are used to optimize the sparse distribution of uniform linear array,matching degree,and operation time.Otherwise,arrayelement position of sparse array pattern and expected pattern are compared to judge the optimization performance of the algorithm.The matrix beam algorithm and its improved algorithm are used to optimize the sparse distribution of the uniform linear array.By comparing the above optimization results,the algorithm with the best optimization performance can be obtained.Finally,a 9×9 array antenna is thinly optimized by using unitary matrix beam algorithm.In the simulation software HFSS,the 9×9 array antenna and the antenna unit are modeled and simulated,and the gain of the antenna unit is multiplied by the array factor in the unitary matrix beam algorithm.After sparse array optimization,the number,arrangement and excitation of sparse array are obtained.Then,the sparse array is modeled and simulated in HFSS,and the radiation characteristics of 9×9 array and sparse array are compared to verify the practicability and accuracy of the algorithm.