Research On Comprehensive Technology Of Sparse Array

Compared with full array with the same aperture,sparse array antenna can achieve the same main beam width with fewer antenna elements,and also has stronger directivity.Therefore,the sparse array antenna has been widely studied and has important application value in practical engineering.The synthesis of sparse arrays is mainly divided into two research directions.The first is minimizing the number of array elements to achieve sparse reconstruction pattern when given the size of the aperture and the reference pattern.The second goal is to reduce the peak sidelobe level by optimizing the position and excitation of array element under fixed number and aperture of array elements.This article focuses on above two directions,the main work is as follows:(1)Aiming at the synthesis of sparse array reconstruction,this article propose methods based on the compressed sensing(CS)sparse reconstruction algorithm.By constructing a virtual array,the sparse array element minimization problem is converted into a sparse signal reconstruction problem.Because the iterative convex optimization algorithm needs to set update parameters manually in the process of solving sparse signal reconstruction,the model is difficult to solve and the algorithm is less robust.Therefore,an adaptive iterative update method is proposed,and simulations verify that the algorithm is suitable for synthesizing different types of linear sparse arrays.At the same time,the algorithm is also suitable for sparse planar arrays.(2)After slacking the sparse array reconstruction model to a l₁ norm problem,it is necessary to estimate the model error in advance,which leads to the setting of the error directly affecting the convergence of the model solution.This paper uses ADMM algorithm to solve the comprehensive model of the sparse array,and simulates the uniform linear array and the non-uniform linear array respectively.Simulation results verify that the algorithm also achieves accurate reconstruction in sparse planar array synthesis.(3)Aiming at the problem of reducing peak sidelobe level of the sparse array,the water circulation optimization algorithm is introduced.Because the water cycle algorithm(WCA)is easy to fall into the local optimal,a stream intrusion behavior is proposed to expand the algorithm's feasible solution space.At the same time,the exponentially decreasing iterative step size is used to ensure the algorithm's early exploration ability and late convergence ability.Moreover,in the simulation process of classic verification function,the WCA and its improvements show better performance in solving multi-dimensional problems.(4)By separating the positions of antenna array elements,the search space for the feasible solution of the model is reduced and the synthesis of sparse linear arrays and sparse planar arrays is converted to water circle algorithm optimization problem.The WCA and the improved WCA are used to solve the problem.Compared with the simulation results of the genetic algorithm(GA),our method shows better application prospect in the sparse array synthesis problem.