Research On Sparse Optimization Method Of Conformal Array Antenna

Conformal array antenna can not only maintain the aerodynamic characteristics of the carrier,but also easy to realize wide-angle scanning and reduce the cross-sectional area of radar scattering.It is widely used in ships,missiles,satellites,aircraft and other fields.However,the large number of array elements increases the design complexity,cost and weight of the array system.The sparse design of the array can optimize the radiation performance of the array while reducing the number of array elements,which has huge ap-plication requirements and research value.Taking conformal array as the research object,thesis studies the sparse optimization method of conformal array.The research is divided into two aspects:least element sparse array optimization and low sidelobe sparse array optimization.Thesis focuses on how to arrange conformal arrays under the constraint of minimum array element spacing.The specific work is as follows:1.The conformal array is affected by the curvature of the carrier,and the maximum energy radiation direction of each array element is inconsistent.In thesis,the rotation transformation is used to realize the transformation of the element pattern between the lo-cal coordinate system and the global coordinate system,and the construction of the pattern function under different conditions of element pointing is completed.At the same time,the occlusion effect of the conformal array is analyzed.Finally,the influence of the par-ticularity of conformal array on the pattern is verified by the joint simulation of MATLAB and HFSS.2.The sparse optimization of the minimum number of elements of conformal array is studied.Using compressive sensing theory,the sparsest problem under the constraints of ar-ray element spacing is transformed into an alternately solved minimum l₁norm optimiza-tion problem.The algorithm includes two convex optimization processes,the first step is cell excitation optimization,and the second step is cell spacing optimization.The two optimization processes influence each other and cross each other.Finally,the method is applied to the sparse synthesis of single-beam and multi-beam conformal arrays.The simulation results verify that the algorithm can achieve a high degree of fitting with the reference pattern with the least number of array elements.Compared with the full array,the sparse array elements are reduced by nearly 20%.3.The optimization of low sidelobe sparsity of conformal array is studied.(1)Aiming at the”premature”problem of the classical genetic algorithm,thesis pro-poses an improved algorithm that evolves in two stages.In the first stage,the crossover position is determined by chaotic search,and the fixed mutation rate is modified to a dy-namic value that changes adaptively with iteration and fitness value?In the second stage,the multi population coevolution strategy is adopted and the immigration operation is in-troduced.Finally,the improved genetic algorithm proposed in thesis is used to optimize the sparse of cylindrical and hemispherical conformal arrays with the goal of minimum sidelobe.The simulation results show that the sparse array not only greatly reduces the number of array elements,but also reduces the peak sidelobe to varying degrees.(2)For the sparse optimization of large conformal arrays,based on the principle of aperture projection and the theory of sparse probability density,a hybrid algorithm(AP-PDS)is proposed.The algorithm projects the conformal array onto a plane to obtain the projection array,then synthesizes the plane array by using the non-uniform Fourier trans-form to obtain the excitation weight,and finally carries out the low sidelobe sparse opti-mization of the conformal array based on the probability density,while the array elements are reduced by 50%,the maximum sidelobe is reduced by 7.8d B.The hybrid algorithm is very efficient and is especially suitable for sparse optimization of large conformal arrays.