Research On Optimization Technology Of Multi Model Sparse Array Antenna

With the development of science and technology,antenna plays an important role in radar system.The radiation characteristics of antenna directly affect the performance of radar system.Compared with other types of antennas,the sparse array antenna has higher degree of freedom,which can not only reduce the number of array elements required,but also obtain excellent directional characteristics.It not only reduces the cost of antenna construction,but also improves the radar system signal receiving and anti-jamming ability.In this paper,the basic knowledge of array antenna is introduced,and the pattern functions of linear array,single ring array and concentric ring array are briefly introduced,which lays a theoretical foundation for the follow-up research.Secondly,according to the structure characteristics of single ring array,an Improved Differential Evolution with Recombination of Margin Code Technique(IDE-RMCT)is proposed.On the basis of IDE-RMCT,the algorithm dynamically updates the population gene search space in the iterative process.At the same time,the corresponding variation variables are generated according to the best quality genome in the iterative process,and the optimal solution is selected and updated according to the advantages and disadvantages of the peak side lobe level.The algorithm not only improves the search efficiency,but also obtains the global optimal solution in a limited number of iterations.Compared with the results obtained by other algorithms,it is shown that the peak sidelobe level is obviously optimized by this algorithm.Then,according to the structural characteristics of concentric ring array,an Modified Particle Swarm Optimization(MPSO)algorithm is proposed and applied to the optimization of concentric ring array.Based on the Particle Swarm Optimization(PSO),the adaptive mutation operation is added in the algorithm,which not only ensures that the high-quality particles are not destroyed,but also improves the diversity of the particle population.By comparing the results with those obtained in other literatures,it is shown that this method can not only obtain lower peak sidelobe level,but also effectively reduce the number of array elements,which is conducive to the cost control of the system.Finally,compressed sensing technology is used to optimize the linear array and concentric ring array,and the SL0 algorithm is used to solve the sparse signal,and the known pattern is reconstructed with less array elements.Combined with CVX solver,MPSO-CVX algorithm is proposed to jointly optimize element position and element excitation in linear array,as well as element radius and excitation amplitude of concentric ring array.The simulation results show that the peak sidelobe level can be greatly reduced by this method,which proves the effectiveness of the algorithm.