Research On The Optimization Algorithm Of Sparse Circular Arrays

Sparse arrays have broad application prospect,especially in the field which has a very high demand to main beam width which is extreme narrow,whereas has an extremely low demand to high gain.Sparse array antennas can use less elements to meet the required radiation characteristics,simplify the feed network,and reduce the system complexity,thus reduce the cost.Due to the random distribution of sparse array antenna elements in the aperture range,the scanning beam is more narrow,the spatial resolution can be improved,element-interaction is reduced.All these advantages make the pattern synthesis technology of sparse array antennas become a hot research topic in recent years.In the paper,aimed at multi constrained of array aperture,array elements number and array elements spacing,differential evolution algorithm optimizes array element position to get peak side lobe level as low as possible.To minimize array elements number as the target,compressed sensing algorithm achieves the synthesis of sparse array antennas pattern,to achieve a more excellent performance of the antenna pattern.The main contents and innovations:Firstly,this paper expounds the basic concepts of array antennas,summaries array antenna synthesis problems,deduces the pattern function of uniform single circle array and uniform concentric ring array,and analyses some characteristics of uniform circular array by simulation.Secondly,this paper discusses the basic concept,algorithm flowchart,and various methods of mutation and crossover operation of differential evolution algorithm.The optimization models of sparse single circle array and sparse concentric ring array are established.Revised differential evolution algorithm is raised to meet multi constraints of element spacing,array aperture and array element number,and the method is applied to two optimization models,lower side lobe level is acquired compared with methods in literatures,the layout of array is better in the range of array aperture.The method improves the degree of freedom of the array layout,reduces the search space of the variables in the algorithm,speeds up the calculation speed of the algorithm,and has strong convergence performance.Thirdly,this paper briefly introduces the basic content of compressed sensing algorithm,including signal sparse decomposition,measurement matrix design and signal reconstruction algorithm.;then the background and algorithm flowchart of split Bregman algorithm are introduced in detail.According to the synthesis problem of sparse array optimization to minimize the number of array elements,split Bregman compressed sensing algorithm is proposed to the synthesis of sparse single ring array and sparse concentric ring array,this method transforms from the problem of array synthesis into the problem of sparse signal reconstruction problem of compressed sensing,a comprehensive models of sparse single circle array and sparse concentric ring array are established,array elements number and array element position are solved by split Bregman method.This method can obtain more performance of pattern,can effectively reduce sparse array antennas elements number,accelerate the speed of iterative processing,can be iterated to the optimal solution quickly.